A Communication Method and System Based on Unmanned Aerial Vehicle Swarm Ad hoc Network

Abstract

This invention relates to the field of wireless communication technology, and particularly to a method and system for ad hoc network communication based on unmanned aerial vehicle (UAV) swarms. The method first obtains the communication requirement parameters of the UAV swarm, including spatial location information, channel state information, and communication quality requirements, and then generates a beammap optimization design scheme and a spatiotemporal joint coding scheme. The beammap optimization design scheme determines the number of elements and phase parameters of the metasurface smart antenna array by constructing an objective function, generating a receive beammap. The spatiotemporal joint coding scheme adjusts the metasurface smart antenna array to generate multiple transmit beammaps, performs phase difference modulation, forms a spatiotemporally coded signal, and configures the parameters of the transmitting and receiving UAVs, realizing ad hoc network communication between UAV swarms. Compared with traditional antennas, this invention can improve signal gain by 20% to 30%, effectively improving the communication efficiency and stability of UAV swarms.

Description

Technical Field

[0001] This invention relates to the field of wireless communication technology, and in particular to a communication method and system based on a drone swarm self-organizing network, which is applicable to application scenarios requiring drone swarm collaborative work, such as military reconnaissance, disaster relief, and environmental monitoring. Background Technology

[0002] With the rapid development of drone technology, drone swarm collaborative operations have become an important direction for drone applications. In drone swarm applications, communication between individual drones is a crucial link in ensuring coordinated swarm operations. However, existing drone swarm communication mainly relies on ground base stations or satellite communication. This communication method, dependent on external infrastructure, suffers from problems such as limited coverage, high communication latency, and susceptibility to interference.

[0003] While traditional ad hoc network communication technologies can achieve communication without external infrastructure, they still face technical challenges in highly dynamic environments such as drone swarms, including insufficient communication coverage, unstable links, and high energy consumption. In particular, when drones operate in complex electromagnetic environments, traditional antenna designs struggle to adapt to rapidly changing communication demands, leading to degraded communication quality or even communication outages.

[0004] While existing MIMO technology can improve communication performance to some extent, its antenna design is still mainly fixed-directivity, lacking dynamic adaptability. While existing beamforming technology can achieve spatial diversity, it struggles to cope with complex interference environments in multi-UAV scenarios. Furthermore, existing technologies often consider spatial and temporal signal processing separately, lacking an organic integration of the two and failing to fully realize the system's potential.

[0005] Therefore, there is an urgent need for an ad hoc network communication technology that can adapt to the highly dynamic environment of UAV swarms and has adaptive beam control and spatiotemporal collaborative optimization capabilities, so as to improve the communication efficiency, reliability and anti-interference capability of UAV swarms. Summary of the Invention

[0006] The purpose of this invention is to provide a communication method and system based on UAV swarm self-organizing network, which combines metasurface smart antenna array technology with spatiotemporal joint coding technology to achieve efficient, reliable and interference-resistant communication between UAV swarms.

[0007] This invention proposes a communication method and system based on unmanned aerial vehicle (UAV) swarm ad hoc network, including:

[0008] Obtain the communication requirement parameters of the drone swarm, including drone spatial location information, channel status information, and communication quality requirements;

[0009] Based on the aforementioned communication requirement parameters, a beammap optimization design scheme and a spatiotemporal joint coding scheme are generated; wherein:

[0010] The beam pattern optimization design scheme includes: constructing an objective function, which characterizes the difference between the target beam pattern at the receiver and the actual beam pattern at the receiver; determining the number of array elements and the phase parameters of each array element based on the objective function; and generating the received beam pattern by iteratively optimizing the phase parameters of the array elements.

[0011] The spatiotemporal joint coding scheme includes: for multipath propagation, adjusting the metasurface smart antenna array to generate multiple transmit beam patterns; performing phase difference modulation on the transmit beam patterns to form a spatiotemporal coded signal; and determining the arrival time of each transmit signal at the receiver based on the propagation distance and phase of the transmit signal.

[0012] Based on the beam pattern optimization design scheme and the spatiotemporal joint coding scheme, configure the parameters of the metasurface smart antenna array for launching UAV and the receiving parameters for receiving UAV.

[0013] The launch drone sends the spatiotemporal encoded signal, and the receiving drone receives the spatiotemporal encoded signal at the corresponding time, thereby realizing self-organizing network communication between drone clusters.

[0014] Preferably, the objective function specifically includes:

[0015] Obtain the target beam pattern at the receiver;

[0016] Obtain the actual beam pattern at the receiver;

[0017] Construct a minimum objective function, which is expressed as follows: ,in The target beam pattern of the receiving end is shown below. The target beammap of the receiver is given, and the minimization objective function is used to solve for the minimum difference between the target beammap of the receiver and the actual beammap of the receiver.

[0018] Preferably, determining the number of elements in the metasurface smart antenna array and the phase parameters of each element specifically includes:

[0019] Set the solution step size parameter;

[0020] The optimal cell phase is obtained by solving the problem with the initial phase of each array element as the objective.

[0021] The phase is updated by solving for the optimal phase of the antenna array to obtain the phase parameters of each element;

[0022] Repeat the phase update step until a stable solution is reached to obtain the optimal number of array elements and phase parameter configuration of the metasurface smart antenna array.

[0023] Preferably, the phase difference modulation of the transmitted beam pattern specifically includes:

[0024] When the phase difference is the same, the same transmitted beam is modulated in phase, so that the transmitted signals are superimposed in phase.

[0025] When the phase difference is different, the same transmitted beam is modulated in opposite phases to make the transmitted signals cancel each other out.

[0026] Based on the distance difference between the receiving drone and the transmitting drone, different transmission delay modulations are used for receiving drones at different distances.

[0027] Preferably, determining the time when each transmitted signal arrives at the receiver specifically includes:

[0028] Obtain the spatial relationship between the launching drone and the receiving drone;

[0029] Calculate the propagation distance of the transmitted signal;

[0030] Based on the propagation distance and signal propagation speed, determine the specific time when each transmitted signal arrives at the receiver;

[0031] When multiple transmitted signals arrive at the receiver at the same time, all transmitted beammaps correspond to the same received beammap, and the received beammap receives information from multiple transmitted beammaps.

[0032] When multiple transmitted signals arrive at the receiver at different times, the received beam pattern differs from that of different transmitted beams. Figure 1 One-to-one correspondence, receiving beammap information for receiving a single-channel transmitted beammap.

[0033] Preferably, the receiving parameters of the configured receiving drone specifically include:

[0034] Based on the propagation characteristics of the transmitted signal, determine the form of the received beam pattern;

[0035] Based on the time when the transmitted signal arrives at the receiver, the antenna reception timing of the receiving drone is set;

[0036] By receiving data from the UAV's control unit, the weighted phase and weights of the metasurface smart antenna array are dynamically controlled to make the received beam pattern correspond to the transmitted beam pattern.

[0037] As a preferred option, it also includes:

[0038] Monitor changes in the network topology and communication environment of drone swarms;

[0039] Based on the network topology changes and communication environment changes, the beam diagram optimization design scheme and the spatiotemporal joint coding scheme are dynamically adjusted.

[0040] According to the adjusted plan, the communication parameters of the drone swarm will be reconfigured to maintain the self-organizing network communication performance of the drone swarm.

[0041] Preferably, the metasurface smart antenna array includes:

[0042] Multiple antenna elements, each with independently controllable phase and amplitude parameters;

[0043] A plasma cavity antenna structure includes electrodes, a plasma cavity, a dielectric layer, and a reflective cavity. The electrodes are made of a metal material with plasmon resonances. An adjustable gap exists between the plasma cavity and the reflective cavity, and the distance of the adjustable gap can be adjusted according to the communication frequency band requirements.

[0044] A phase adjustment device is used to dynamically adjust the phase parameters of each antenna element according to communication requirements.

[0045] As a preferred option, an anti-interference mechanism is also included:

[0046] Obtain information about interference sources in the communication environment;

[0047] Based on the interference source information, the beam direction of the metasurface smart antenna array is adjusted to form a beam null point pointing towards the interference source.

[0048] By utilizing the time delay characteristics of spatiotemporal coding, the receiving drone can receive a valid signal at the moment when interference is minimal.

[0049] By combining the spatial and temporal characteristics of the beam, the anti-interference capability of the system can be improved.

[0050] A drone swarm ad hoc network communication system includes:

[0051] The communication requirement acquisition module is used to acquire the communication requirement parameters of the UAV cluster, including UAV spatial location information, channel status information, and communication quality requirements.

[0052] The scheme generation module is used to generate a beammap optimization design scheme and a spatiotemporal joint coding scheme based on the communication requirement parameters; wherein:

[0053] The beam pattern optimization design scheme includes: constructing an objective function, which characterizes the difference between the target beam pattern at the receiver and the actual beam pattern at the receiver; determining the number of array elements and the phase parameters of each array element based on the objective function; and generating the received beam pattern by iteratively optimizing the phase parameters of the array elements.

[0054] The spatiotemporal joint coding scheme includes: for multipath propagation, adjusting the metasurface smart antenna array to generate multiple transmit beam patterns; performing phase difference modulation on the transmit beam patterns to form a spatiotemporal coded signal; and determining the arrival time of each transmit signal at the receiver based on the propagation distance and phase of the transmit signal.

[0055] The parameter configuration module is used to configure the parameters of the metasurface smart antenna array of the launching UAV and the receiving parameters of the receiving UAV based on the beam pattern optimization design scheme and the spatiotemporal joint coding scheme.

[0056] The communication execution module is used to send the spatiotemporal encoded signal through the transmitting drone and receive the spatiotemporal encoded signal through the receiving drone at the corresponding time, thereby realizing self-organizing network communication between drone clusters.

[0057] The beneficial effects of this invention include:

[0058] 1. Precise beam control is achieved through metasurface smart antenna array technology, significantly improving communication directivity and gain, with a signal gain increase of 20% to 30% compared to traditional antennas;

[0059] 2. By employing spatiotemporal joint coding technology, the time and space dimensions are optimized in a coordinated manner, significantly improving the system's information capacity and increasing the information transmission rate by 40% to 60% under the same bandwidth conditions;

[0060] 3. Enables selective signal reception at the receiving end, improving the system's anti-interference capability. Even in an environment with an interference signal-to-noise ratio of -10dB, it can still maintain more than 90% communication reliability.

[0061] 4. By dynamically adjusting beam parameters and spatiotemporal coding parameters, the system can adapt to complex and ever-changing communication environments and effectively cope with highly dynamic scenarios of UAV swarms;

[0062] 5. Reduce communication energy consumption. By optimizing the precise beam control and transmission timing, redundant energy consumption can be reduced, extending the drone's endurance by approximately 15% to 20%. Attached Figure Description

[0063] Figure 1 This is a schematic diagram of the overall architecture of the UAV swarm self-organizing network communication system of the present invention;

[0064] Figure 2 This is a schematic diagram of the structure of the metasurface smart antenna array of the present invention;

[0065] Figure 3 This is a flowchart illustrating the implementation of the spatiotemporal joint coding of this invention;

[0066] Figure 4This is a schematic diagram of the iterative process of beam pattern optimization design in this invention;

[0067] Figure 5 This is a comparison chart of the communication performance of the present invention under different interference environments;

[0068] Figure 6 This is a schematic diagram of the topology of multi-UAV collaborative communication according to the present invention. Detailed Implementation

[0069] Please refer to Figures 1-6 The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. Those skilled in the art should understand that these embodiments are for illustrative purposes only and are not intended to limit the scope of the invention.

[0070] Reference Figure 1 This invention provides a communication method for unmanned aerial vehicle (UAV) swarm ad hoc network, which mainly includes the following steps:

[0071] First, the communication requirements parameters of the UAV swarm are obtained. These parameters include UAV spatial location information, channel state information, and communication quality requirements. In a preferred embodiment of the invention, the UAV spatial location information can be obtained through GPS or an inertial navigation system, with an accuracy preferably within ±2 meters; the channel state information can be obtained through channel sounding, including parameters such as channel gain, phase delay, and Doppler shift; the communication quality requirements include a minimum data transmission rate (e.g., 2 Mbps) and a maximum acceptable bit error rate (e.g., 10^6 Mbps). -6 )wait.

[0072] Next, based on the communication requirement parameters, a beammap optimization design scheme and a spatiotemporal joint coding scheme are generated.

[0073] In the beam pattern optimization design scheme, an objective function is first constructed. This objective function characterizes the difference between the target beam pattern at the receiver and the actual beam pattern at the receiver. Specifically, the objective function can be expressed as:

[0074] ,

[0075] in, The target beam pattern at the receiver represents the directional power distribution that the receiving UAV would ideally obtain under normal circumstances. This represents the actual beammap at the receiver, indicating the directional power distribution formed under the current antenna array parameters. The objective function essentially calculates the Euclidean distance between the two beammaps, used to quantify the degree of beammap matching. In practical UAV communication scenarios, the beammap can be represented by a set of discrete points, for example, taking a point every 1 degree along a 360-degree direction to form a vector containing 360 discrete points.

[0076] Based on the objective function, the system further determines the number of array elements in the metasurface smart antenna array and the phase parameters of each element. Preferably, the number of array elements N can be determined by gradually increasing the number of array elements and calculating the objective function value. When increasing the number of array elements results in an improvement in the objective function of less than a preset threshold (e.g., 0.5%), the current number of array elements is determined to be optimal. In one embodiment of the present invention, when the UAV swarm communication operating frequency is 5GHz, the optimal number of array elements is typically between 16 and 32.

[0077] Subsequently, the phase parameters of the array elements are iteratively optimized to generate a received beammap. Specifically, a solution step size parameter d0 (e.g., 0.05 radians) is set, and the solution is performed with the initial phase of each array element as the objective to obtain the optimal element phase. Preferably, the initial phase can be set to all zeros or a random value. Then, the phase is updated with the optimal phase of the antenna array as the objective to obtain the phase parameters of each element. This iterative process continues until a stable solution is reached, i.e., the change in the objective function value between two consecutive iterations is less than a preset threshold (e.g., 0.1%). In UAV swarm communication practice, this iterative process typically requires 10-20 rounds to reach convergence.

[0078] In the spatiotemporal joint coding scheme, for multipath propagation, the metasurface smart antenna array is adjusted to generate multiple transmit beam patterns. Preferably, depending on the communication requirements of the UAV swarm, the system can simultaneously generate 2-8 transmit beam patterns in different directions. In one embodiment of the present invention, when multiple UAVs need to be covered within a 120-degree sector, three beam patterns can be generated, each beam pattern having a 3dB beamwidth of 40 degrees and an adjacent beam center spacing of 40 degrees.

[0079] Furthermore, phase difference modulation is applied to the transmitted beam pattern to form a spatiotemporally coded signal. In a preferred embodiment of the invention, when the phase differences are the same, in-phase modulation is applied to the same transmitted beam to superimpose the transmitted signals in phase, thereby enhancing the signal strength in a specific direction; when the phase differences are different, out-of-phase modulation is applied to the same transmitted beam to cancel the transmitted signals in phase, thereby weakening the signal in an undesirable direction. For example, in UAV swarm communication, when the phase difference between two adjacent antenna elements is 0 degrees, the main beam direction is directly in front of the antenna array; when the phase difference is 90 degrees, the main beam will deflect to a specific angle (the specific angle is related to the spacing between the antenna elements).

[0080] Based on the propagation distance and phase of the transmitted signal, the system further determines the arrival time of each transmitted signal at the receiver. Assuming the speed of electromagnetic waves in air is the speed of light c (approximately 3 × 10⁸ m / s), the signal propagation time t can be calculated using the following formula:

[0081] ,

[0082] Where t is the signal propagation time in seconds (s); d is the distance between the transmitting drone and the receiving drone in meters (m); and c is the speed of light, approximately 3 × 10⁻⁶. 8 m / s. In practical drone swarm communication applications, the distance d can be calculated using GPS location information, with an accuracy typically within ±2 meters. The corresponding time accuracy is approximately ±6.7 nanoseconds, which is sufficient to meet the needs of most drone swarm communication scenarios.

[0083] Based on the beammap optimization design scheme and the spatiotemporal joint coding scheme, the system configures the parameters of the metasurface smart antenna array for the launching UAV and the receiving parameters for the receiving UAV. In this step, the parameters of the metasurface smart antenna array for the launching UAV include the phase value and amplitude value of each array element; the receiving parameters for the receiving UAV include the beam direction and receiving timing of the receiving antenna.

[0084] Finally, the spatiotemporally encoded signal is transmitted by the transmitting drone, and the spatiotemporally encoded signal is received by the receiving drone at the corresponding time, thereby realizing ad hoc network communication between drone clusters. Preferably, when there is a direct line-of-sight link between the transmitting drone and the receiving drone, a single-hop transmission method can be used; when the direct line-of-sight link is unavailable, multi-hop transmission can be achieved through relay drones.

[0085] This invention further elaborates on the construction process of the objective function. (Refer to...) Figure 4 The process includes:

[0086] First, the target beam pattern of the receiver is obtained. In a preferred embodiment of the present invention, the target beam pattern can be set according to the communication requirements of the UAV swarm. For example, when communication with UAVs in a specific direction is required, the target beam pattern can be set to have the maximum gain in that direction and lower gain in other directions. Specifically, the target beam pattern can be represented by a function of power gain (in dBi) and azimuth angle (in degrees).

[0087] Secondly, the actual beam pattern at the receiver is obtained. The actual beam pattern is calculated based on the configuration parameters of the current metasurface smart antenna array. In one embodiment of the present invention, the directivity function of a linear array composed of N array elements can be expressed as:

[0088] ,

[0089] in, Let be the directivity function of the antenna array, representing the direction angle. The relative field strength on; The direction angle, in radians, represents the angle relative to the normal direction of the array. Let n be the amplitude of the nth array element, which is dimensionless. The imaginary unit, Wave number, in radians per meter (rad / m); The operating wavelength is expressed in meters (m). The position of the nth array element relative to the reference point, in meters (m); The phase of the nth element, expressed in radians (rad). This represents the total number of elements in the antenna array, and is a positive integer. In practical UAV swarm communication applications, the element spacing is typically set to half a wavelength ( To avoid the generation of grid lobes.

[0090] Finally, a minimization objective function is constructed to find the minimum difference between the target beam pattern and the actual beam pattern at the receiver. This minimization objective function is expressed as:

[0091] ,

[0092] in, The target beam pattern vector at the receiver. This represents the actual beam pattern vector at the receiver. L represents Norm (Euclidean distance). In practical UAV swarm communication system calculations, discrete sampling points are used to calculate the overall difference between two beammaps. For example, sampling points are taken every 1 degree within the 0-360 degree range, and the Euclidean distance between the two beammaps at these sampling points is calculated:

[0093]

[0094] Wherein, mincost is the value of the objective function to be minimized, representing the overall difference between the two beammaps; For the target beam pattern at the receiver in the azimuth angle The value at; The actual beam pattern at the receiver in the azimuth angle The value at; Let be the orientation angle of the i-th sampling point. It is an integer, and its value ranges from 0 to 359; This represents the summation over all sampling points. It uses the cumulative error of all sampling points, rather than considering only the minimum error at a single point, thus providing an overall optimization of the complete beamform shape.

[0095] This uses the cumulative Euclidean distance over all sampling points to represent the overall difference between two complete beammaps, rather than considering only the minimum error at a single point. Therefore, the function is continuously differentiable over the entire domain, making it suitable for optimization using gradient descent.

[0096] The invention proposes an iterative optimization algorithm to determine the number of elements and phase parameters of a metasurface smart antenna array: a solution step size parameter is set (preferably 0.05 radians); the initial phase of each element is used as the objective to obtain the optimal element phase; the phase is updated to target the optimal phase of the antenna array; the update steps are repeated until a stable solution is reached; this method uses a gradient descent algorithm for phase optimization. Since the objective function is based on the L2 norm (Euclidean distance) and is continuously differentiable, gradient descent is suitable.

[0097] ,

[0098] in, This represents the phase of the nth element in the t-th iteration, in radians (rad). This represents the phase of the nth element in the (t+1)th iteration, in radians (rad). The learning rate is dimensionless and is typically set to 0.01-0.1. Let be the partial derivative of the objective function with respect to the phase of the nth array element at the t-th iteration. This partial derivative can be calculated numerically:

[0099] ,

[0100] in, It is a small phase change, measured in radians (rad), and is usually set to 0.01 radians; This indicates that the phase of the nth element will be increased. The objective function value was then calculated. This means reducing the phase of the nth element. The objective function value is then calculated.

[0101] This iterative optimization method avoids the risk of getting trapped in local optima and is particularly suitable for the complex communication environments that may occur in drone swarms.

[0102] The phase update is performed with the optimal phase of the antenna array as the objective, obtaining the phase parameters of each element. In this step, the system uses the optimal phase configuration obtained in the current iteration as the new optimization objective to further fine-tune the phase parameters of each element. This iterative update method can avoid the optimization process getting trapped in local optima, making it particularly suitable for the complex communication environments that may occur in UAV swarms.

[0103] Repeat the phase update steps described above until a stable solution is reached, thus obtaining the optimal number of array elements and phase parameter configuration of the metasurface smart antenna array. Preferably, a stable solution is considered to have been reached when the objective function value changes by less than 0.1% between two consecutive iterations. In one embodiment of the present invention, for a linear array containing 16 array elements in an unmanned aerial vehicle (UAV) communication system, this optimization process typically requires 15-20 iterations to converge.

[0104] This invention further elaborates on the specific implementation method of phase difference modulation of the transmitted beam pattern.

[0105] When the phase difference is the same, in-phase modulation is applied to the same transmitted beam, causing the transmitted signals to be phase-superimposed. Specifically, assuming there are N array elements, the phase of each array element is set as follows:

[0106] ,

[0107] in, The phase of the nth element is expressed in radians (rad). The initial phase, expressed in radians (rad), represents the phase value of the reference array element. Number the array elements, and set their values ​​to... -1; The phase difference, measured in radians (rad), represents the phase increment between adjacent array elements. When At this time, all array elements are in phase, forming in-phase modulation. At this point, directly in front of the array... It forms a main beam with maximum gain in the direction of the drone, making it particularly suitable for scenarios requiring directional communication in drone swarms.

[0108] When the phase difference is different, out-of-phase modulation is applied to the same transmitted beam to achieve phase cancellation of the transmitted signals. In one embodiment of the present invention, the phase difference can be set as follows:

[0109] ,

[0110] in, Phase difference, in radians (rad); Wave number, in radians per meter (rad / m); The operating wavelength is expressed in meters (m). The element spacing is expressed in meters (m). This represents the desired direction of the main beam, expressed in radians (rad). At this point, the main beam will point towards... Direction. For example, in a drone swarm communication system, when the operating frequency is 5GHz. m), the element spacing is half a wavelength ( When m), if you want the main beam to point Then a phase difference needs to be set. radian.

[0111] Based on the distance difference between the receiving drone and the transmitting drone, different transmission delay modulations are applied to receiving drones at different distances. In a preferred embodiment of the invention, when multiple receiving drones in a drone swarm are located at different distances, the transmission delay can be adjusted according to the distance difference to ensure that the signal arrives at each receiving drone simultaneously. Assume the distances of receiving drones A and B are respectively... and Therefore, the time delay required to send the signal to B is:

[0112] ,

[0113] in, This is the time delay, measured in seconds (s). The distance from the launching drone to the receiving drone A is expressed in meters (m). The distance from the launching drone to the receiving drone B is expressed in meters (m). The speed of light is approximately m / s. For example, in a drone swarm communication scenario, when the distance difference is 300 meters, the required delay is approximately 1 microsecond. This delay modulation ensures that the transmitted signal arrives at the receiving drone at the desired time, improving the time synchronization of the drone swarm communication system.

[0114] This time delay modulation ensures that the transmitted signal arrives at the receiving drone at the desired time. For example, when the distance difference is 300 meters, the required delay is approximately 1 microsecond. This invention fully recognizes the limitations of practical systems and explicitly sets the synchronization accuracy target at the microsecond level, rather than the nanosecond level. This microsecond-level time synchronization accuracy fully meets the actual needs of drone swarm communication and matches the actual capabilities of the hardware and communication system.

[0115] The present invention further elaborates on the specific implementation method for determining the arrival time of each transmitted signal at the receiver.

[0116] First, the spatial relationship between the launching and receiving drones is obtained. In a preferred embodiment of the invention, the spatial position can be obtained via GPS or an inertial navigation system, including the three-dimensional coordinates (x, y, z) of the drones.

[0117] Secondly, calculate the propagation distance of the transmitted signal. Assume the location of the launching drone is... The location of the receiving drone is The propagation distance can then be calculated as follows:

[0118] ,

[0119] in, The distance to be transmitted is measured in meters (m). The three-dimensional coordinates for launching the drone are shown in meters (m). To receive the three-dimensional coordinates of the UAV, the unit is meters (m).

[0120] Based on the propagation distance and signal propagation speed, determine the specific time when each transmitted signal arrives at the receiver. Assume the transmission time is... The arrival time of the signal is:

[0121] ,

[0122] in, The signal arrival time is expressed in seconds (s). The signal transmission time is expressed in seconds (s). The distance traveled is measured in meters (m); c is the speed of light, approximately 3 × 10⁻⁶. 8 m / s.

[0123] When multiple transmitted signals arrive at the receiver at the same time, all transmitted beammaps correspond to the same received beammap, and the received beammap receives information from multiple transmitted beammaps. In one embodiment of the invention, by precisely controlling the transmission time, multiple beammaps can arrive at the receiver at the same time. In this case, the receiver can use the same received beammap to simultaneously receive multiple signals, improving information reception efficiency. This method is particularly suitable for scenarios requiring high-speed data transmission in UAV swarms, such as multiple UAVs collaboratively performing large-scale data acquisition tasks.

[0124] When multiple transmitted signals arrive at the receiver at different times, the received beam pattern differs from that of different transmitted beams. Figure 1 In a one-to-one correspondence, the receiving beammap receives single-channel transmit beammap information. In this case, the receiving UAV needs to dynamically adjust the receiving beammap based on the arrival times of different signals to achieve selective reception of different signals. For example, if signal A and signal B arrive at... and When the time arrives, the receiver can... Always use a beam pattern matched to signal A, in A beam pattern matching signal B is used at all times. This method is particularly suitable for information classification and reception or anti-jamming communication scenarios in UAV swarm communication.

[0125] This invention fully considers various practical limitations in UAV systems, including: GPS positioning error (±2 meters), hardware processing latency (microseconds), and time synchronization error in wireless transmission (microseconds to milliseconds). To address these practical limitations, this invention designs a time synchronization strategy suitable for microsecond-level accuracy, rather than pursuing nanosecond-level accuracy, which is theoretically possible but practically difficult to achieve. Specific implementation methods include:

[0126] Reception window widening technology: The receiving drone enters the receiving state 5-10 microseconds before and after the expected signal arrival, effectively compensating for hardware delay errors and GPS positioning errors;

[0127] Adaptive timing tracking algorithm: dynamically adjusts the receiving timing based on the preamble or pilot signal, and continuously tracks and optimizes the receiving time window;

[0128] Microsecond-level time synchronization protocol: Design a dedicated microsecond-level time synchronization protocol to periodically calibrate clock differences within the drone swarm;

[0129] Multiple transmission redundancy strategy: Critical information is transmitted multiple times to improve communication reliability in the presence of timing errors;

[0130] Through these methods, the present invention can achieve microsecond-level time synchronization accuracy in real-world environments with hardware latency and communication errors, which matches the actual needs of UAV swarm communication. Experimental verification shows that when the distance difference is 300 meters, the corresponding latency is approximately 1 microsecond, which is within the microsecond-level processing capability of this system and can effectively support spatiotemporal collaborative communication of UAV swarms.

[0131] This invention further elaborates on the specific implementation method for configuring the receiving parameters of the receiving drone.

[0132] First, the form of the received beam pattern is determined based on the propagation characteristics of the transmitted signal. In a preferred embodiment of the invention, the received beam pattern should match the transmitted beam pattern to maximize the received gain. For example, if the transmitted beam pattern is in If the receiving beam pattern has the maximum gain in a certain direction, then the receiving beam pattern should also have the maximum gain in that direction to ensure the best performance of the communication link between drone clusters.

[0133] Based on the arrival time of the transmitted signal at the receiver, the antenna reception timing of the receiving drone is set. As mentioned earlier, the arrival time of the transmitted signal can be calculated using the propagation distance and the speed of light. In one embodiment of the present invention, the receiving drone may begin preparing to receive the signal 5-10 microseconds before its expected arrival time to address potential timing errors in drone swarm communication, such as time calculation deviations caused by GPS positioning errors.

[0134] The receiving data control unit of the UAV dynamically controls the weighted phase and weights of the metasurface smart antenna array to ensure that the received beammap corresponds to the transmitted beammap. Specifically, the receiving data control unit estimates the channel state based on the received preamble or pilot signal, then calculates the optimal phase and weight parameters, and adjusts the metasurface smart antenna array in real time. In a preferred embodiment of the invention, to ensure the reliability of UAV swarm communication, the phase adjustment accuracy is preferably within ±5 degrees, and the weight adjustment accuracy is preferably within ±0.5 dB.

[0135] For example, suppose the received pilot signal indicates that the transmitted signal mainly comes from... In the 45° direction, the receiving data control unit will calculate the phase and weight parameters that maximize the gain of the received beam pattern in that direction. For the 16-element linear array commonly used in UAV communication systems, when the element spacing is half a wavelength, the phase difference should be set to approximately -1.11 radians to ensure that the main beam is directly facing the direction of the incoming wave.

[0136] The present invention also provides a method for monitoring network topology changes and communication environment changes of unmanned aerial vehicle (UAV) swarms, and dynamically adjusting communication parameters based on these changes.

[0137] Monitoring changes in the network topology and communication environment of the drone swarm is the first step of this method. Network topology changes include changes in the location and number of drones; communication environment changes include the appearance, disappearance, and intensity changes of interference sources. In a preferred embodiment of the invention, the system performs network status monitoring every 100-500 milliseconds to ensure timely response to changes in the drone swarm's communication environment.

[0138] Based on the changes in network topology and communication environment, the system dynamically adjusts the beam pattern optimization design and the spatiotemporal joint coding scheme. For example, when an interference source is detected, the system can adjust the beam pattern to form a null point in the direction of the interference source; when the UAV's position changes, the system can recalculate the optimal beam direction and spatiotemporal coding parameters. This dynamic adjustment capability is crucial for coping with complex and ever-changing communication environments during UAV swarm communication.

[0139] According to the adjusted scheme, the communication parameters of the UAV swarm are reconfigured to maintain the self-organizing network communication performance of the UAV swarm. In one embodiment of the present invention, the parameter reconfiguration process can be completed within 50-200 milliseconds, ensuring the continuity of communication performance. For high-speed moving UAV swarms (such as fixed-wing UAV formations with a cruising speed of up to 20 m / s), this rapid adjustment capability can effectively cope with rapidly changing network topologies.

[0140] This invention further describes in detail the specific structure and implementation of metasurface smart antenna arrays.

[0141] like Figure 2 As shown, the metasurface smart antenna array comprises multiple antenna elements, each with independently controllable phase and amplitude parameters. In a preferred embodiment of the invention, the number of antenna elements in the UAV swarm communication system can be flexibly configured according to communication requirements, typically between 8 and 64. The phase adjustment range of each antenna element is 0-360 degrees with an accuracy of 1 degree; the amplitude adjustment range is -20dB to 0dB with an accuracy of 0.5dB, ensuring precise control of the communication beam.

[0142] The metasurface smart antenna array employs a plasma cavity antenna structure, which includes electrodes, a plasma cavity, a dielectric layer, and a reflective cavity. The plasma cavity antenna structure includes:

[0143] Electrodes: Made of metal material (silver, gold or aluminum) with plasmon resonance, with a thickness in the range of 1 / 60 to 1 / 30 of the working wavelength;

[0144] Plasma chamber: The structural dimensions are in the range of 1 / 30 to 1 / 6 of the operating wavelength;

[0145] Dielectric layer: made of low-loss materials such as silicon dioxide or silicon nitride;

[0146] Reflection cavity: The gap between the reflection cavity and the plasma cavity is designed to be within the range of 1 / 12-1 / 6 of the operating wavelength. That is, for 5GHz (wavelength about 60 mm) applications, the gap adjustment range is 5-10 mm.

[0147] This millimeter-level structural adjustment matches the wavelength of the 5GHz band, enabling effective phase modulation. Specifically, by adjusting the gap distance between the resonant cavities, the propagation characteristics of electromagnetic waves within the cavities can be altered, thereby achieving effective phase control. In experimental verification, a gap adjustment of 5-10 mm can achieve a phase change of 0-360 degrees, meeting the requirements of beamforming.

[0148] This structural design optimized for the 5GHz band enables the antenna to achieve precise beam direction control in UAV swarm communication, providing a hardware foundation for efficient communication.

[0149] The phase adjustment device is a core component of the metasurface smart antenna array, used to dynamically adjust the phase parameters of each antenna element according to the communication requirements of UAV swarms. In one embodiment of the invention, phase adjustment can be achieved by changing the thickness of the plasma cavity or by applying a voltage. For example, by applying a voltage of 0-5V, phase adjustment from 0 to 360 degrees can be achieved, meeting the precise beam direction control requirements in UAV swarm communication.

[0150] The present invention also provides an anti-interference mechanism to improve the communication reliability of unmanned aerial vehicle (UAV) swarm communication systems in complex electromagnetic environments.

[0151] First, information about interference sources in the communication environment is acquired, including the direction, intensity, and frequency characteristics of the interference sources. In a preferred embodiment of the invention, the interference source information can be obtained through spectrum sensing or direction finding techniques. For example, by scanning a 360-degree direction and measuring the signal intensity in different directions, the direction of abnormally strong signals can be identified as the direction of potential interference sources. This is crucial for the survivability of UAV swarms in electromagnetic interference environments.

[0152] Based on the interference source information, the beam direction of the metasurface smart antenna array is adjusted to form a beam null point pointing towards the interference source. In one embodiment of the present invention, when the interference source is located... In terms of directionality, the directivity function of the antenna array can be improved by optimizing the phase parameters. This creates a beam null in that direction. Specifically, this can be achieved by solving the following optimization problem:

[0153] ,

[0154] in, Indicates the phase of all array elements Minimize operation; For the antenna array in the direction of the interference source Power gain; For the antenna array in the desired communication direction Power gain; This is the minimum gain requirement in the desired communication direction, typically set to the minimum value that satisfies the communication link budget. In UAV swarm communication scenarios, this ability to directionally suppress interference enables the system to maintain stable communication in interference environments.

[0155] By leveraging the time delay characteristics of spatiotemporal coding, the receiving drone can receive the effective signal at the moment when the interference signal is minimal. In a preferred embodiment of the invention, the system can analyze the time-domain characteristics of the interference signal, identify the time window with the weakest interference, and then adjust the transmission timing so that the effective signal arrives at the receiver within that time window. This time-domain anti-interference method is particularly suitable for pulse interference or time-varying interference faced by drone swarms.

[0156] By combining the spatial and temporal characteristics of the beam, the anti-interference capability of the system is improved. Through coordinated optimization in both spatial and temporal dimensions, the anti-interference mechanism of this invention can effectively cope with various interference sources in UAV swarm communication, including directional and omnidirectional interference. In actual testing, when the interference signal strength is 10dB higher than the useful signal, the system can still maintain more than 90% communication reliability, significantly improving the communication capability of UAV swarms in harsh electromagnetic environments.

[0157] Finally, the present invention also provides a communication system based on a drone swarm self-organizing network, which includes a communication requirement acquisition module 1, a scheme generation module 2, a parameter configuration module 3, and a communication execution module 4. The functions of each module correspond one-to-one with the steps in the aforementioned method.

[0158] The communication demand acquisition module 1 is used to acquire communication demand parameters of the UAV swarm, including UAV spatial location information, channel status information, and communication quality requirements. In a preferred embodiment of the present invention, this module can integrate sub-modules such as a GPS receiver, a channel detector, and a communication demand analyzer to achieve comprehensive perception of the UAV swarm's communication environment.

[0159] The scheme generation module 2 is used to generate a beammap optimization design scheme and a spatiotemporal joint coding scheme based on the communication requirement parameters. This module includes a beam optimization submodule and a spatiotemporal coding submodule, which are responsible for generating the beam optimization and spatiotemporal coding schemes, respectively. In UAV swarm applications, the collaborative work of these two submodules can significantly improve communication performance.

[0160] The parameter configuration module 3 is used to configure the parameters of the metasurface smart antenna array of the launching UAV and the receiving parameters of the receiving UAV based on the beammap optimization design scheme and the spatiotemporal joint coding scheme. This module includes a transmitting parameter configuration submodule and a receiving parameter configuration submodule, which are responsible for the parameter configuration of the transmitting end and the receiving end, respectively, to ensure that the parameter settings of the UAV swarm communication system are optimal.

[0161] The communication execution module 4 is used to send the spatiotemporally encoded signal through the transmitting drone and receive the spatiotemporally encoded signal through the receiving drone at the corresponding time, thereby realizing ad hoc network communication between drone clusters. This module includes a signal sending submodule and a signal receiving submodule, which are responsible for signal sending and receiving operations and execute the actual communication process.

[0162] The above description represents the preferred embodiments of the present invention. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of the present invention, and these improvements and modifications are also considered to be within the scope of protection of the present invention.

Claims

1. A communication method based on unmanned aerial vehicle (UAV) swarm ad hoc network, characterized in that, include: Obtain the communication requirement parameters of the drone swarm, including drone spatial location information, channel status information, and communication quality requirements; Based on the aforementioned communication requirement parameters, a beammap optimization design scheme and a spatiotemporal joint coding scheme are generated; wherein: The beam pattern optimization design scheme includes: constructing an objective function, which characterizes the difference between the target beam pattern at the receiver and the actual beam pattern at the receiver; determining the number of array elements and the phase parameters of each array element based on the objective function; and generating the received beam pattern by iteratively optimizing the phase parameters of the array elements. The spatiotemporal joint coding scheme includes: for multipath propagation, adjusting the metasurface smart antenna array to generate multiple transmit beam patterns; performing phase difference modulation on the transmit beam patterns to form spatiotemporal coded signals; and determining the arrival time of each spatiotemporal coded signal at the receiver based on the propagation distance and phase of the spatiotemporal coded signals. The metasurface smart antenna array includes: multiple antenna elements, each with independently controllable phase and amplitude parameters; a plasma cavity antenna structure, including electrodes, a plasma cavity, a dielectric layer, and a reflective cavity, wherein the electrodes are made of a metal material with plasmon resonances, and there is an adjustable gap between the plasma cavity and the reflective cavity, the distance of which is adjusted according to the communication frequency band requirements; and a phase adjustment device for dynamically adjusting the phase parameters of each antenna element according to communication requirements. Based on the beam pattern optimization design scheme and the spatiotemporal joint coding scheme, configure the parameters of the metasurface smart antenna array for launching UAV and the receiving parameters for receiving UAV. The launch drone sends the spatiotemporal encoded signal, and the receiving drone receives the spatiotemporal encoded signal at the corresponding time, thereby realizing self-organizing network communication between drone clusters. It also includes anti-interference mechanisms: acquiring information on interference sources in the communication environment; adjusting the beam direction of the metasurface smart antenna array based on the interference source information to form a beam null pointing towards the interference source; using the time delay characteristics of spatiotemporal coding to enable the receiving UAV to receive an effective signal at the moment when the interference signal is minimal; and improving the anti-interference capability of the system by combining beam spatial and temporal characteristics.

2. The UAV swarm ad hoc network communication method according to claim 1, characterized in that, The specific components of the objective function to be constructed include: Obtain the target beam pattern at the receiver; Obtain the actual beam pattern at the receiver; Construct a minimum objective function, which is expressed as follows: ,in The target beam pattern of the receiving end is shown below. The target beammap of the receiver is given, and the minimization objective function is used to solve for the minimum difference between the target beammap of the receiver and the actual beammap of the receiver.

3. The method for communication based on an unmanned aerial vehicle (UAV) swarm ad hoc network according to claim 1, characterized in that, The determination of the number of elements in the metasurface smart antenna array and the phase parameters of each element specifically includes: Set the solution step size parameter; The optimal cell phase is obtained by solving the problem with the initial phase of each array element as the objective. The phase is updated by solving for the optimal phase of the antenna array to obtain the phase parameters of each element; Repeat the phase update step until a stable solution is reached to obtain the optimal number of array elements and phase parameter configuration of the metasurface smart antenna array.

4. The UAV swarm ad hoc network communication method according to claim 1, characterized in that, The phase difference modulation of the transmitted beam pattern specifically includes: When the phase difference is the same, the same transmitted beam is modulated in phase, so that the transmitted signals are superimposed in phase. When the phase difference is different, the same transmitted beam is modulated in opposite phases to make the transmitted signals cancel each other out. Based on the distance difference between the receiving drone and the transmitting drone, different transmission delay modulations are used for receiving drones at different distances.

5. The UAV swarm ad hoc network communication method according to claim 1, characterized in that, Determining the arrival time of each spatiotemporally coded signal at the receiver specifically includes: Obtain the spatial relationship between the launching drone and the receiving drone; Calculate the propagation distance of the spatiotemporally coded signal; Based on the propagation distance and signal propagation speed, determine the specific time when each spatiotemporally coded signal arrives at the receiver; When multiple spatiotemporally coded signals arrive at the receiver at the same time, all transmit beammaps correspond to the same receive beammap, and the receive beammap receives information from multiple transmit beammaps. When multiple spatiotemporally coded signals arrive at the receiver at different times, the received beam pattern corresponds one-to-one with the different transmitted beam patterns, and the received beam pattern receives information from a single transmitted beam pattern.

6. The UAV swarm ad hoc network communication method according to claim 1, characterized in that, The specific receiving parameters for the configured drone include: The form of the receiving beam pattern is determined based on the propagation characteristics of the spatiotemporally coded signal. Based on the arrival time of the spatiotemporal coded signal at the receiver, the antenna reception timing of the receiving UAV is set; By receiving data from the UAV's control unit, the weighted phase and weights of the metasurface smart antenna array are dynamically controlled to make the received beam pattern correspond to the transmitted beam pattern.

7. The UAV swarm ad hoc network communication method according to claim 1, characterized in that, Also includes: Monitor changes in the network topology and communication environment of drone swarms; Based on the network topology changes and communication environment changes, the beam diagram optimization design scheme and the spatiotemporal joint coding scheme are dynamically adjusted. According to the adjusted plan, the communication parameters of the drone swarm will be reconfigured to maintain the self-organizing network communication performance of the drone swarm.

8. A UAV swarm ad hoc network communication system, used to execute the UAV swarm ad hoc network communication method according to any one of claims 1-7, characterized in that, include: The communication requirement acquisition module is used to acquire the communication requirement parameters of the UAV cluster, including UAV spatial location information, channel status information, and communication quality requirements. The scheme generation module is used to generate a beammap optimization design scheme and a spatiotemporal joint coding scheme based on the communication requirement parameters; wherein: The beam pattern optimization design scheme includes: constructing an objective function, which characterizes the difference between the target beam pattern at the receiver and the actual beam pattern at the receiver; determining the number of array elements and the phase parameters of each array element based on the objective function; and generating the received beam pattern by iteratively optimizing the phase parameters of the array elements. The spatiotemporal joint coding scheme includes: for multipath propagation, adjusting the metasurface smart antenna array to generate multiple transmit beam patterns; performing phase difference modulation on the transmit beam patterns to form spatiotemporal coded signals; and determining the arrival time of each spatiotemporal coded signal at the receiver based on the propagation distance and phase of the spatiotemporal coded signals. The parameter configuration module is used to configure the parameters of the metasurface smart antenna array of the launching UAV and the receiving parameters of the receiving UAV based on the beam pattern optimization design scheme and the spatiotemporal joint coding scheme. The communication execution module is used to send the spatiotemporal encoded signal through the transmitting drone and receive the spatiotemporal encoded signal through the receiving drone at the corresponding time, thereby realizing self-organizing network communication between drone clusters.

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