Method and device for joint configuration of trajectory resources in heterogeneous wireless networks of unmanned aerial vehicles

Abstract

The present application relates to a method and device for joint configuration of trajectory resources in a heterogeneous wireless network of unmanned aerial vehicles. The method comprises: obtaining the initial trajectory information and initial communication resource configuration corresponding to the target unmanned aerial vehicle, and determining the initial energy efficiency corresponding to the target unmanned aerial vehicle based on the initial trajectory information and the initial communication resource configuration, that is, performing a first iterative optimization process on the initial trajectory information, the initial communication resource configuration and the initial energy efficiency according to a preset unmanned aerial vehicle configuration model, and obtaining the operation configuration data of the target unmanned aerial vehicle, wherein the unmanned aerial vehicle configuration model is used to optimize the initial trajectory information and the initial communication resource configuration according to the initial energy efficiency. The use of this method can improve the configuration accuracy.

Description

Technical Field

[0001] The present application relates to the field of communication technology, and in particular to a method and device for jointly configuring trajectory resources in a heterogeneous wireless network of unmanned aerial vehicles. Background Art

[0002] In modern network communications, drones are often used to expand coverage due to the inadequacy of network coverage provided by ground stations.

[0003] When using drones to provide network services to users, it is necessary to configure the relevant data of the drones to control their operating trajectory. In related technologies, the configuration of the drones is usually determined based on the area to be covered, thereby planning the operating trajectory of the drones in a two-dimensional plane so that the drones can provide network services to users in the area to be covered.

[0004] However, the above-mentioned UAV configuration method has the problem of low configuration accuracy. Summary of the invention

[0005] Based on this, it is necessary to provide a method and device for jointly configuring trajectory resources in heterogeneous wireless networks of unmanned aerial vehicles, which can improve planning accuracy, in response to the above technical problems.

[0006] In a first aspect, the present application provides a method for jointly configuring trajectory resources in a heterogeneous wireless network of unmanned aerial vehicles, comprising:

[0007] Obtaining initial trajectory information and initial communication resource configuration corresponding to the target UAV, and determining the initial energy efficiency corresponding to the target UAV based on the initial trajectory information and the initial communication resource configuration;

[0008] Determine intermediate trajectory information and intermediate communication resource configuration according to the initial trajectory information, the initial communication resource configuration, and an inner loop model included in the UAV configuration model;

[0009] Determine intermediate energy efficiency based on intermediate trajectory information, intermediate communication resource configuration, and an outer loop model included in the UAV configuration model;

[0010] determining whether the first iterative optimization process is finished according to the intermediate energy efficiency, and if the first iterative optimization process is finished, determining the intermediate trajectory information and the intermediate communication resource configuration as the operation configuration data;

[0011] Among them, the drone configuration model is used to optimize the initial trajectory information and initial communication resource configuration according to the initial energy efficiency.

[0012] In one embodiment, the drone configuration model includes an inner loop model and an outer loop model. According to the preset drone configuration model, the initial trajectory information, the initial communication resource configuration, and the initial energy efficiency are first iteratively optimized to obtain the operation configuration data of the target drone, including:

[0013] Determine intermediate trajectory information and intermediate communication resource configuration according to the initial trajectory information, the initial communication resource configuration and the inner loop model;

[0014] determining intermediate energy efficiency based on intermediate trajectory information, intermediate communication resource configuration, and an outer loop model;

[0015] It is determined whether the first iterative optimization process is completed according to the intermediate energy efficiency. If the first iterative optimization process is completed, the intermediate trajectory information and the intermediate communication resource configuration are determined as the operation configuration data.

[0016] In one embodiment, the method further comprises:

[0017] If the first iterative optimization process is not completed, the first iterative optimization process is continued for the intermediate trajectory information, intermediate communication resource configuration, and intermediate energy efficiency according to the UAV configuration model until the operation configuration data is obtained.

[0018] In one embodiment, determining the intermediate trajectory information and the intermediate communication resource configuration according to the initial trajectory information, the initial communication resource configuration and the inner loop model includes:

[0019] The inner loop model is used to perform a second iterative optimization process on the initial communication resource configuration and the inner loop model to obtain intermediate trajectory information and intermediate communication resource configuration.

[0020] In one embodiment, the initial communication resource configuration and the inner loop model are subjected to a second iterative optimization process using the inner loop model to obtain intermediate trajectory information and intermediate communication resource configuration, including:

[0021] Optimizing the initial trajectory information and the initial communication resource configuration according to the inner loop model to obtain optimized trajectory information and optimized communication resource configuration;

[0022] Determining whether the second iterative optimization process is completed according to the optimized trajectory information and the optimized communication resource configuration;

[0023] If the second iterative optimization process is finished, the optimized trajectory information is used as the intermediate trajectory information, and the optimized communication resource configuration is used as the intermediate communication resource configuration;

[0024] If the second iterative optimization process is not finished, the optimized trajectory information and the optimized communication resource configuration are continuously optimized according to the inner loop model until an intermediate communication resource configuration is obtained.

[0025] In one embodiment, the initial communication resource configuration includes an initial user scheduling configuration, an initial transmission power configuration, and an initial transmission bandwidth configuration. The initial trajectory information and the initial communication resource configuration are optimized according to the inner loop model to obtain the optimized trajectory information and the optimized communication resource configuration, including:

[0026] According to the first sub-problem model, the initial trajectory information, the initial transmission power configuration and the initial transmission bandwidth configuration included in the inner loop model, an optimized user scheduling configuration is obtained;

[0027] According to the second sub-problem model, the optimized user scheduling configuration, the initial transmission power configuration and the initial transmission bandwidth configuration included in the inner loop model, the optimized trajectory information is obtained;

[0028] According to the third sub-problem model included in the inner loop model, the optimized user scheduling configuration, the optimized trajectory information and the initial transmission power configuration, an optimized transmission bandwidth configuration is obtained;

[0029] According to the fourth sub-problem model, the optimized user scheduling configuration, the optimized trajectory information and the optimized transmission bandwidth configuration included in the inner loop model, an optimized transmission power configuration is obtained.

[0030] In a second aspect, the present application also provides a device for jointly configuring trajectory resources in a heterogeneous wireless network of unmanned aerial vehicles, including:

[0031] An acquisition module is used to acquire initial trajectory information and initial communication resource configuration corresponding to the target UAV, and determine the initial energy efficiency corresponding to the target UAV according to the initial trajectory information and the initial communication resource configuration;

[0032] A configuration module, the configuration module comprising an inner loop unit, configured to determine intermediate trajectory information and intermediate communication resource configuration according to the initial trajectory information, the initial communication resource configuration, and the inner loop model included in the drone configuration model; an outer loop unit, configured to determine intermediate energy efficiency according to the intermediate trajectory information, the intermediate communication resource configuration, and the outer loop model included in the drone configuration model; a first iteration ending unit, configured to determine whether a first iteration optimization process is ended according to the intermediate energy efficiency, and if the first iteration optimization process is ended, determining the intermediate trajectory information and the intermediate communication resource configuration as operation configuration data;

[0033] Among them, the drone configuration model is used to optimize the initial trajectory information and initial communication resource configuration according to the initial energy efficiency.

[0034] In a third aspect, an embodiment of the present application provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the method of the first aspect when executing the computer program.

[0035] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of the method of the first aspect described above.

[0036] In a fifth aspect, the present application further provides a computer program product, wherein the computer program product comprises a computer program, and when the computer program is executed by a processor, the steps of the method in the first aspect are implemented.

[0037] The above-mentioned method and device for joint configuration of trajectory resources in heterogeneous wireless networks of unmanned aerial vehicles, by obtaining the initial trajectory information and initial communication resource configuration corresponding to the target unmanned aerial vehicle, and determining the initial energy efficiency corresponding to the target unmanned aerial vehicle according to the initial trajectory information and initial communication resource configuration, can perform a first iterative optimization process on the initial trajectory information, initial communication resource configuration and initial energy efficiency according to a preset unmanned aerial vehicle configuration model, and obtain the operation configuration data of the target unmanned aerial vehicle, wherein the unmanned aerial vehicle configuration model is used to optimize the initial trajectory information and initial communication resource configuration according to the initial energy efficiency. In this way, when configuring the operation of the target unmanned aerial vehicle, the energy efficiency generated by the target unmanned aerial vehicle during operation is comprehensively considered, and the initial trajectory information and initial communication resource configuration are iteratively optimized through the preset unmanned aerial vehicle configuration model to obtain the final operation configuration data, thereby avoiding the problem of inaccurate configuration in the traditional technology of determining the configuration of the unmanned aerial vehicle only according to the area to be covered, and planning the operation trajectory of the unmanned aerial vehicle in a two-dimensional plane. The technical solution provided by the present application comprehensively considers the energy efficiency problem generated by the target unmanned aerial vehicle during operation and optimizes the trajectory information and communication resource configuration, so that the final operation configuration data is more accurate and the energy efficiency is more optimized. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] In order to more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the drawings required for use in the embodiments of the present application or related technical descriptions will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0039] Figure 1A diagram of an application environment of a method for jointly configuring trajectory resources in a heterogeneous wireless network of unmanned aerial vehicles in an embodiment;

[0040] Figure 2 This is a diagram of an actual application scenario after the target drone moves in one embodiment.

[0041] Figure 3 It is a flowchart of a method for jointly configuring trajectory resources in a heterogeneous wireless network of unmanned aerial vehicles in one embodiment;

[0042] Figure 4 is a flow chart of step 302 in another embodiment;

[0043] Figure 5 A schematic diagram of a process for obtaining intermediate trajectory information and configuring intermediate communication resources in another embodiment;

[0044] Figure 6 It is a structural block diagram of a trajectory resource joint configuration device in a heterogeneous wireless network of unmanned aerial vehicles in one embodiment;

[0045] Figure 7 FIG. 4 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0046] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0047] With the rapid development of B5G and 6G, users have an increasing demand for higher data rates and the sharing and utilization of massive information. In modern communication networks, due to the shortcomings of ground stations in network coverage, the coverage is usually expanded.

[0048] Drones are used to expand the coverage of network communications due to their low cost, fast deployment, fully controllable mobility, strong line-of-sight communication advantages, and flexible path-finding capabilities. Therefore, when using drones to provide network services to users, the drones need to be configured to control their operating trajectory.

[0049] In the related technology, the configuration of the drone is usually determined according to the scope of the area to be covered, so as to plan the operation trajectory of the drone in a two-dimensional plane so that the drone can provide network services to users in the area to be covered. However, the two-dimensional trajectory does not take into account constraints such as the coverage range of the drone and the obstacle avoidance of the drone. The existing technology of optimizing the three-dimensional trajectory of the drone through configuration does not take into account the energy efficiency problem brought about by the three-dimensional movement of the drone.

[0050] Therefore, the above-mentioned joint configuration method of trajectory resources in heterogeneous wireless networks of UAVs has the problem of low configuration accuracy.

[0051] In view of this, the present application provides a method and device for jointly configuring trajectory resources in a heterogeneous wireless network of unmanned aerial vehicles. By obtaining the initial trajectory information and initial communication resource configuration corresponding to the target unmanned aerial vehicle, and determining the initial energy efficiency corresponding to the target unmanned aerial vehicle according to the initial trajectory information and initial communication resource configuration, the initial trajectory information, initial communication resource configuration and initial energy efficiency can be optimized for the first iteration according to the preset unmanned aerial vehicle configuration model to obtain the operation configuration data of the target unmanned aerial vehicle, wherein the unmanned aerial vehicle configuration model is used to optimize the initial trajectory information and initial communication resource configuration according to the initial energy efficiency. In this way, when configuring the operation of the target unmanned aerial vehicle, the energy efficiency generated by the target unmanned aerial vehicle during operation is comprehensively considered, and the initial trajectory information and initial communication resource configuration are iteratively optimized through the preset unmanned aerial vehicle configuration model to obtain the final operation configuration data, thereby avoiding the problem of inaccurate configuration in the traditional technology of determining the configuration of the unmanned aerial vehicle only according to the area to be covered, and planning the operation trajectory of the unmanned aerial vehicle in a two-dimensional plane. The technical solution provided by the present application comprehensively considers the energy efficiency problem generated by the target unmanned aerial vehicle during operation and optimizes the trajectory information and communication resource configuration, so that the final operation configuration data is more accurate and the energy efficiency is more optimized.

[0052] The method for jointly configuring trajectory resources in a heterogeneous wireless network of unmanned aerial vehicles provided in the embodiment of the present application can be applied to Figure 1 In the application environment shown. Among them, the target drone 102 can communicate with multiple users 104. User 104 can be a real-time user who needs to maintain a communication connection with the target drone all the time, or a non-real-time user who maintains a communication connection with the target drone in several time slots. Among them, the terminal device corresponding to user 104 can be but not limited to various personal computers, laptops, smart phones, tablets, Internet of Things devices and portable wearable devices. The Internet of Things devices can be smart speakers, smart TVs, smart air conditioners, smart car devices, projection devices, etc. Portable wearable devices can be smart watches, smart bracelets, head-mounted devices, etc. Head-mounted devices can be virtual reality (VR) devices, augmented reality (AR) devices, smart glasses, etc.

[0053] Reference Figure 2 , which is the actual application scenario diagram after the target UAV moves.

[0054] In an exemplary embodiment, Figure 3 As shown, a method for joint configuration of trajectory resources in heterogeneous wireless networks of unmanned aerial vehicles is provided, and the method is applied to Figure 1 The target UAV in the example is used to illustrate, including the following steps 301 and 302. Among them:

[0055] Step 301: Acquire initial trajectory information and initial communication resource configuration corresponding to the target UAV, and determine the initial energy efficiency corresponding to the target UAV according to the initial trajectory information and the initial communication resource configuration.

[0056] The target UAV may be a UAV waiting to be configured. The target UAV may obtain initial trajectory information and initial communication resource configuration. In an embodiment of the present application, the trajectory information may include three-dimensional trajectory information corresponding to the target UAV within a preset time period, and the initial trajectory information is the trajectory information initialized according to certain preset rules; the communication resource configuration may characterize the relevant communication configuration of the target UAV when providing network communication services to users within the coverage area, such as user scheduling configuration, transmission power configuration, and transmission bandwidth configuration. The user scheduling configuration may characterize users who are connected to the target UAV for communication within a preset time period. Users include real-time users and non-real-time users. Real-time users are users who maintain communication connections with the target UAV, and non-real-time users are users who maintain communication connections with the target UAV within a preset time slot; the transmission power configuration represents the transmission power allocated by the target UAV to each user; the transmission bandwidth configuration represents the bandwidth allocated by the target UAV to each user; the initial communication resource configuration is the communication resource configuration initialized according to certain preset rules.

[0057] Optionally, the target UAV can generate initial trajectory information and initial communication resource configuration by itself according to preset rules; optionally, the target UAV can use the result of historical configuration as the current initial trajectory and initial communication resource configuration.

[0058] Regarding the trajectory information, it can be recorded as Q={q t ,0≤t ≤T}, where q t =(x t ,y t ,h t ), 0-T is the preset time period, (x t ,y t ,h t ) is the position coordinate of the target UAV at time t, x t is the x-axis coordinate of the target drone at time t, y t is the coordinate of the target drone on the y axis at time t, z t is the coordinate of the target UAV on the z-axis at time t.

[0059] If the communication resource configuration includes user scheduling configuration, transmission power configuration and transmission bandwidth configuration, the user scheduling configuration can be recorded as X={x t,k,0≤t ≤T, k∈K}, where t represents time t, k represents the user ID, K is the set of all users, x k,t is whether the communication status between the target UAV and user k is connected at time t. If it is connected, then x k,t is t, otherwise, x k,t =0, output power configuration; transmission power configuration can be recorded as P={p t,k ,0≤t ≤T, k∈K}, where p t,k represents the power transmitted by the target UAV to user k at time t; the corresponding transmission bandwidth configuration can be recorded as S={s t,k ,0≤t ≤T, k∈K}, where s t,k represents the bandwidth allocated by the target UAV to k users at time t.

[0060] Based on the above initial communication resource configuration and initial trajectory information, the corresponding initial energy efficiency can be determined.

[0061] In one possible implementation, the target UAV can substitute the initial communication resource configuration and initial trajectory information into a pre-trained network model to obtain the initial energy efficiency of the model output.

[0062] In another possible implementation, the target UAV may obtain a formula related to calculating energy efficiency, and substitute the initial communication resource configuration and initial trajectory information into the formula to obtain the initial energy efficiency.

[0063] In the embodiment of the present application, energy efficiency is used to characterize the amount of information that a target drone unit can transmit, which can be expressed as the following formula:

[0064] EE=R / E (1)

[0065] Among them, EE is energy efficiency, E is the total system power consumption, and R is the total system throughput.

[0066] The calculation formula of the total system throughput R can refer to the following formula:

[0067] (2)

[0068] Among them, R t,k represents the data transmission rate between the target UAV and user k at time t, which can be calculated according to the following formula:

[0069] (3)

[0070] in, is the signal-to-noise ratio received by user k at time t.

[0071] The calculation formula of the total system power consumption E can refer to the following formula:

[0072] (4)

[0073] in, is the propulsion energy consumption of the target UAV at time t, and the calculation formula can refer to the following formula:

[0074] (5)

[0075] Among them, c 1 is the first preset parameter related to the area of ​​the target UAV wing, c 2 It is the second preset parameter related to the air density of the target drone. g is the acceleration due to gravity, and its standard value is 9.8m / s 2 , v t is the speed of the target UAV at time t, a t is the acceleration of the target UAV at time t.

[0076] Substituting the initial user scheduling configuration, initial transmission power configuration, and initial transmission bandwidth configuration into the above formula, the initial energy efficiency corresponding to the target UAV can be determined.

[0077] Step 302: Perform a first iterative optimization process on the initial trajectory information, initial communication resource configuration, and initial energy efficiency according to a preset UAV configuration model to obtain the operation configuration data of the target UAV.

[0078] Among them, the drone configuration model is used to optimize the initial trajectory information and initial communication resource configuration according to the initial energy efficiency.

[0079] In a possible implementation, the target UAV may directly input the initial trajectory information, initial communication resource configuration, and initial energy efficiency into a pre-trained iterative optimization model for iterative optimization processing, thereby obtaining the operating configuration data output by the model.

[0080] In another possible implementation, after obtaining the initial trajectory information, initial communication resource configuration, and initial energy efficiency, the target UAV may use energy efficiency as an objective function, and continuously optimize the initial trajectory information and initial communication resource configuration according to pre-set constraints, thereby obtaining the trajectory information and communication resource configuration corresponding to the optimized energy efficiency. The target UAV may use the trajectory information and communication resource configuration corresponding to the optimized energy efficiency as the target UAV's operating configuration data, and the operating configuration data may be used to control the operation of the target UAV.

[0081] In the above embodiment, when configuring the operation of the target UAV, the energy efficiency generated during the operation of the target UAV is comprehensively considered, and the initial trajectory information and the initial communication resource configuration are iteratively optimized through a preset UAV configuration model to obtain the final operation configuration data. This avoids the problem of inaccurate configuration in the traditional technology of only determining the configuration plan of the UAV according to the area to be covered and planning the operation trajectory of the UAV in a two-dimensional plane. The technical solution provided by the present application comprehensively considers the energy efficiency problems generated during the operation of the target UAV and optimizes the trajectory information and communication resource configuration, so that the final operation configuration data is more accurate and the energy efficiency is more optimized.

[0082] In one embodiment, based on the above Figure 3 The embodiment shown, see Figure 4 , this embodiment involves a process of performing a first iteration optimization process on the initial trajectory information, initial communication resource configuration, and initial energy efficiency according to a preset drone configuration model to obtain the operation configuration data of the target drone. In this embodiment, the drone configuration model includes an inner loop model and an outer loop model, such as Figure 4 As shown, step 302 may include steps 401 to 403 .

[0083] Step 401, determining intermediate trajectory information and intermediate communication resource configuration according to the initial trajectory information, the initial communication resource configuration and the inner loop model included in the drone configuration model.

[0084] In an embodiment of the present application, the target drone can determine the objective function based on energy efficiency, take the trajectory information and communication resource configuration as sub-problems, and obtain the drone configuration model based on the constraints corresponding to each sub-problem.

[0085] After establishing the UAV configuration model, the target UAV can decompose the UAV configuration model into an inner loop model and an outer loop model, wherein the outer loop model can be a model that takes energy efficiency as the objective function, trajectory information and communication resource configuration as parameters to be optimized, and the inner loop model includes trajectory information and sub-problem models corresponding to each communication resource configuration. In an embodiment of the present application, the target UAV can first iteratively optimize the initial trajectory information and initial communication resource configuration according to the inner loop model to obtain intermediate trajectory information and intermediate communication resource configuration.

[0086] Step 402 , determining the intermediate energy efficiency according to the intermediate trajectory information, the intermediate communication resource configuration, and the outer loop model included in the UAV configuration model.

[0087] After obtaining the intermediate trajectory information and the intermediate communication resource configuration, the target UAV can determine the intermediate energy efficiency corresponding to the current first iterative optimization process according to the intermediate trajectory information, the intermediate communication resource configuration and the objective function (i.e., energy efficiency) set by the outer loop model.

[0088] Step 403 : determining whether the first iterative optimization process is finished according to the intermediate energy efficiency; if the first iterative optimization process is finished, determining the intermediate trajectory information and the intermediate communication resource configuration as the operation configuration data.

[0089] After determining the intermediate energy efficiency corresponding to the current first iterative optimization processing process, the target UAV can determine the corresponding objective function value based on the intermediate energy efficiency to determine whether the first iterative optimization processing process is completed. In a possible implementation, the target UAV can determine whether the first iterative optimization processing process is completed by detecting whether the objective function value reaches a preset threshold. In addition, the target UAV can also determine whether the first iterative optimization processing process is completed by detecting whether the number of iterations corresponding to the current first iterative optimization processing process reaches a preset target.

[0090] Optionally, if the first iterative optimization processing process is completed, the target UAV can determine the intermediate trajectory information and intermediate communication resource configuration as operation configuration data; optionally, if the first iterative optimization processing process is not completed, the target UAV can continue to perform the first iterative optimization processing on the intermediate trajectory information, intermediate communication resource configuration and intermediate energy efficiency according to the UAV configuration model until the operation configuration data is obtained.

[0091] In a possible implementation manner, taking the communication resource configuration including user scheduling configuration, transmission power configuration and transmission bandwidth configuration as an example, the constraint conditions corresponding to the user scheduling configuration may include the following conditions:

[0092] (6)

[0093] in, Targeting drones Moments and Users The horizontal distance between for The coverage radius of the target drone relative to the ground at any moment, is a very large parameter, K 1 is the number of real-time users, K 2 is the number of non-real-time users.

[0094] The constraints corresponding to the transmission power configuration and the transmission bandwidth configuration may include the following conditions:

[0095] (7)

[0096] in, and Represents the maximum transmit power and total bandwidth of the drone.

[0097] Since energy efficiency is the objective function, the data transmission rate R t,k Constraints are as follows:

[0098] (8)

[0099] Among them, R th,k It is the minimum data transmission rate that can be transmitted between the target UAV and the user, determined according to the actual application scenario.

[0100] In the embodiment of the present application, the target UAV's own operating capability is also limited, so the speed and acceleration also have corresponding constraints:

[0101] (9)

[0102] v max represents the maximum speed of the target drone, a max Represents the maximum acceleration of the target drone.

[0103] It is understandable that the flight altitude of the target UAV also needs to be constrained. Therefore, the constraint conditions corresponding to the flight altitude are:

[0104] (10)

[0105] h min is the minimum height, h max is the maximum height, h t is the height of the target UAV at time t.

[0106] For some specific application scenarios, the starting point and end point of the target drone are the same. Therefore, it is also necessary to constrain the starting point and end point of the target drone. The constraints are as follows:

[0107] (11)

[0108] q 0 is the starting point of the target drone, q T is the destination of the target drone. In summary, the target drone can obtain the drone configuration model:

[0109] (12)

[0110] It can be understood that, in order to facilitate the solution, the time discretization technology can be used to divide the preset time period [0, T] into N equal time slots. The length of the time slot is sufficiently small, and the position of the target UAV in each time slot can be approximately unchanged. Therefore, the trajectory information of the UAV can be obtained through the N-dimensional sequence It indicates that the drone configuration model can also be updated as follows:

[0111] (13)

[0112] Correspondingly, the user scheduling configuration can be expressed as X={x n,k ,0≤n ≤N, k∈K}, the transmission power configuration can be recorded as P={p n,k ,0≤n≤N, k∈K}, the transmission bandwidth configuration can be written as S={s n,k ,0≤n ≤N, k∈K}, the trajectory information can be recorded as Q={q n,k , n∈N}.

[0113] In the embodiments of the present application, it can be seen that trajectory information, user scheduling configuration, transmission power configuration and transmission bandwidth configuration are multivariable optimization problems, in which there are non-convex constraints. In order to facilitate calculation, the idea of ​​combining the Dinkelbach iterative algorithm and the block coordinate descent algorithm is adopted to decompose the above problem into an inner loop model and an outer loop model.

[0114] In the embodiment of the present application, since the energy efficiency is in fractional form, the Dinkelbach method can be used to convert the energy efficiency into a subtraction form:

[0115] (14)

[0116] in, is the energy efficiency of the system and it is known that the function About is a monotonically decreasing function of . The energy efficiency is obtained when the trajectory information, user scheduling configuration, transmission power configuration and transmission bandwidth configuration all obtain the optimal solution, so we have:

[0117] (15)

[0118] If and only if hour, Through the above analysis, it is found that solving the maximum energy efficiency is equivalent to finding the auxiliary function The intersection of the horizontal axis and the horizontal axis can be solved using the Dinkelbach algorithm. Therefore, the objective function can be .

[0119] Therefore, the drone configuration model can be updated as follows:

[0120] (16)

[0121] It can be understood that the current UAV configuration model includes an outer loop model with an objective function of F, optimization parameters of trajectory information Q, user scheduling configuration X, transmission power configuration P and transmission bandwidth configuration S. For a first iterative optimization process, the target UAV can obtain the intermediate trajectory information, intermediate user scheduling configuration, intermediate transmission power configuration and intermediate transmission bandwidth configuration output by the inner loop model. The target UAV can obtain the corresponding intermediate energy efficiency according to the intermediate trajectory information, intermediate user scheduling configuration, intermediate transmission power configuration and intermediate transmission bandwidth, and substitute the intermediate energy efficiency into the objective function to obtain the corresponding objective function value. The target UAV can preset the objective function threshold and the maximum number of iterations, and detect whether the objective function value corresponding to the current first iterative optimization process reaches the preset objective function threshold, and whether the number of iterations corresponding to the current first iterative optimization process is greater than the maximum number of iterations. If the objective function value corresponding to the current first iterative optimization process reaches the preset objective function threshold, or the number of iterations corresponding to the current first iterative optimization process is greater than the maximum number of iterations, the target UAV can determine that the first iterative optimization process is over, and determine the intermediate trajectory information and the intermediate communication resource configuration as the running configuration data.

[0122] In a possible implementation, the above iterative solution process can be algorithmized to obtain an algorithm corresponding to the outer loop model. The specific content can be referred to Table 1:

[0123]

[0124] Table 1

[0125] Among them, X 0 For the initial user scheduling configuration, Q 0 is the initial trajectory information, S 0 is the initial transmission bandwidth configuration, P 0 is the initial transmission power configuration, l is the number of iterations of the first iterative optimization process, ε 0 is the initial energy efficiency, η is the preset objective function threshold, l max is the maximum number of iterations.

[0126] For the inner loop model, the target UAV can decompose the above into four sub-problem models: user scheduling information, trajectory information, transmission power configuration and transmission bandwidth configuration according to the block coordinate descent algorithm. The subsequent target UAV can continuously optimize the initial user scheduling configuration, initial trajectory information, initial transmission bandwidth configuration and initial transmission power configuration according to the four sub-problem models included in the inner loop model, so as to obtain the intermediate user scheduling configuration, intermediate trajectory information, intermediate transmission bandwidth configuration and initial transmission power configuration.

[0127] In one embodiment, based on the above Figure 4 The embodiment shown in the figure relates to a process of determining intermediate trajectory information and intermediate communication resource configuration according to initial trajectory information, initial communication resource configuration and inner loop model. Step 401 may include: performing a second iterative optimization process on the initial communication resource configuration and the inner loop model using the inner loop model to obtain intermediate trajectory information and intermediate communication resource configuration.

[0128] In the embodiment of the present application, the target UAV can use the inner loop model to perform a second iterative optimization process on the initial communication resource configuration and the inner loop model to obtain intermediate trajectory information and intermediate communication resource configuration. For the second iterative optimization process, in a possible implementation, refer to Figure 5 , the process may include:

[0129] Step 501 : Optimize the initial trajectory information and the initial communication resource configuration according to the inner loop model to obtain optimized trajectory information and optimized communication resource configuration.

[0130] Step 502: Determine whether the second iterative optimization process is finished according to the optimized trajectory information and the optimized communication resource configuration.

[0131] Step 503: If the second iterative optimization process is finished, the optimized trajectory information is used as the intermediate trajectory information, and the optimized communication resource configuration is used as the intermediate communication resource configuration.

[0132] Step 504: If the second iterative optimization process is not finished, the optimized trajectory information and the optimized communication resource configuration are continuously optimized according to the inner loop model until an intermediate communication resource configuration is obtained.

[0133] For each second iterative optimization process, the target UAV can first optimize the initial trajectory information and the initial communication resource configuration according to the inner loop model to obtain the optimized trajectory information and the optimized communication resource configuration.

[0134] In a possible implementation, the target UAV inputs initial trajectory information and initial communication resource configuration into the inner loop model, and the optimized trajectory information and optimized communication resource configuration output by the inner loop model can be obtained.

[0135] In another possible implementation, the inner loop model may include sub-problem models established for trajectory information and different communication resource configurations. In the embodiment of the present application, taking the drone configuration model of formula (16) as an example, the initial communication resource configuration includes the initial user scheduling configuration, the initial transmission power configuration, and the initial transmission bandwidth configuration. The sub-problem model may include a first sub-problem model corresponding to the user scheduling configuration, a second sub-problem model corresponding to the trajectory information, a third sub-problem model corresponding to the transmission bandwidth configuration, and a fourth sub-problem model corresponding to the transmission power configuration.

[0136] In the embodiment of the present application, the first sub-problem model can refer to the following formula:

[0137] (17)

[0138] The second sub-problem model can refer to the following formula:

[0139] (18)

[0140] It can be seen that since the trajectory information includes multiple parameters to be optimized (coordinate information), that is, the current objective function is a non-convex function, and the current sub-problem model also has a non-convex constraint C1, in order to be able to transform the non-convex problem into a convex problem for solution, in the embodiment of the present application, relaxation and continuous convex approximation techniques are introduced. The basic idea of ​​continuous convex approximation is to obtain the local optimal (suboptimal) solution of the original non-convex problem by replacing the non-convex objectives and constraints of the original non-convex problem with their upper or lower bounds.

[0141] First, according to the first-order Taylor expansion and the second-order Taylor expansion, the approximate relationship between velocity, acceleration and position can be obtained:

[0142] (19)

[0143] Since the original function corresponding to the propulsion energy consumption is non-convex, in order to solve this problem, the slack variable is introduced , the propulsion energy consumption can be rewritten as:

[0144] (20)

[0145] At this time, the energy consumption of propulsion is about It is convex, but it also introduces a non-convex constraint, which can be referred to the following formula:

[0146] (twenty one)

[0147] Therefore, assuming that The speed of the target drone obtained in the iteration is , so we have:

[0148] (twenty two)

[0149] at this time About The linear function of is convex, so the original non-convex constraint can be written as:

[0150] (twenty three)

[0151] Then, in order to solve the non-concavity of throughput and the non-convexity of constraint C1, continuous convex optimization is used to deal with it. Time slots and users The distance between , located at The square of the distance between the target drone and user k obtained in the iteration is , at this time the target drone is Time slots and users The data transmission rate is about is convex, so the lower bound of its first-order Taylor expansion is:

[0152] (twenty four)

[0153] So the objective function can be rewritten as . Then the second sub-problem model can be restated as follows:

[0154] (25)

[0155] The third sub-problem model corresponding to the transmission bandwidth configuration can refer to the following formula:

[0156] (26)

[0157] The fourth sub-problem model corresponding to the transmission power configuration can refer to the following formula:

[0158] (27)

[0159] Based on the above sub-problem models, the initial trajectory information and the initial communication resource configuration are optimized according to the inner loop model to obtain the optimized trajectory information and the optimized communication resource configuration. The process may include: obtaining the optimized user scheduling configuration according to the first sub-problem model, the initial trajectory information, the initial transmission power configuration and the initial transmission bandwidth configuration included in the inner loop model; obtaining the optimized trajectory information according to the second sub-problem model, the optimized user scheduling configuration, the initial transmission power configuration and the initial transmission bandwidth configuration included in the inner loop model; obtaining the optimized transmission bandwidth configuration according to the third sub-problem model, the optimized user scheduling configuration, the optimized trajectory information and the initial transmission power configuration included in the inner loop model; obtaining the optimized transmission power configuration according to the fourth sub-problem model, the optimized user scheduling configuration, the optimized trajectory information and the optimized transmission bandwidth configuration included in the inner loop model.

[0160] In a possible implementation, the above process is coded to obtain an algorithm corresponding to the inner loop model. The specific content can be referred to Table 2:

[0161]

[0162] Table 2

[0163] Among them, r is the number of iterations of the second iterative optimization process, r max is the maximum number of iterations of the second iterative optimization process, ζ is a preset threshold value, when the statistical value of the objective function value calculated corresponding to two adjacent second iterative optimization processes meets the preset threshold value, or the number of iterations of the second iterative optimization process reaches the maximum number of iterations, the target UAV can determine that the second iterative optimization process is completed and obtain the intermediate trajectory information and intermediate communication resource configuration.

[0164] In one embodiment, an exemplary method for jointly configuring trajectory resources in a heterogeneous wireless network of unmanned aerial vehicles is provided, which can be applied to Figure 1 In the implementation environment shown.

[0165] Step a: obtaining initial trajectory information and initial communication resource configuration corresponding to the target UAV, and determining the initial energy efficiency corresponding to the target UAV based on the initial trajectory information and the initial communication resource configuration.

[0166] The initial communication resource configuration includes initial user scheduling configuration, initial transmission power configuration and initial transmission bandwidth configuration.

[0167] Step b: obtaining an optimized user scheduling configuration according to the first sub-problem model, initial trajectory information, initial transmission power configuration and initial transmission bandwidth configuration included in the inner loop model.

[0168] Step c: obtaining optimized trajectory information according to the second sub-problem model, the optimized user scheduling configuration, the initial transmission power configuration and the initial transmission bandwidth configuration included in the inner loop model.

[0169] Step d: obtaining an optimized transmission bandwidth configuration according to the third sub-problem model included in the inner loop model, the optimized user scheduling configuration, the optimized trajectory information and the initial transmission power configuration.

[0170] Step e: obtaining an optimized transmission power configuration according to the fourth sub-problem model included in the inner loop model, the optimized user scheduling configuration, the optimized trajectory information and the optimized transmission bandwidth configuration.

[0171] Step f: determining whether the second iterative optimization process is completed according to the optimized trajectory information and the optimized communication resource configuration.

[0172] Step g: if the second iterative optimization process is finished, the optimized trajectory information is used as the intermediate trajectory information, and the optimized communication resource configuration is used as the intermediate communication resource configuration.

[0173] Step h: If the second iterative optimization process is not finished, the optimized trajectory information and the optimized communication resource configuration are continuously optimized according to the inner loop model until an intermediate communication resource configuration is obtained.

[0174] Step i: determining the intermediate energy efficiency according to the intermediate trajectory information, the intermediate communication resource configuration and the outer loop model.

[0175] Step j: determining whether the first iterative optimization process is finished according to the intermediate energy efficiency; if the first iterative optimization process is finished, determining the intermediate trajectory information and the intermediate communication resource configuration as the operation configuration data.

[0176] Among them, the drone configuration model is used to optimize the initial trajectory information and initial communication resource configuration according to the initial energy efficiency.

[0177] Step k: If the first iterative optimization process is not completed, continue to perform the first iterative optimization process on the intermediate trajectory information, intermediate communication resource configuration, and intermediate energy efficiency according to the UAV configuration model until the operation configuration data is obtained.

[0178] It should be understood that, although the various steps in the flowcharts involved in the above-mentioned embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above-mentioned embodiments can include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0179] Based on the same inventive concept, the embodiment of the present application also provides a device for jointly configuring trajectory resources in a heterogeneous wireless network of unmanned aerial vehicles for implementing the method for jointly configuring trajectory resources in a heterogeneous wireless network of unmanned aerial vehicles involved in the above. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above method, so the specific limitations in the embodiments of one or more devices for jointly configuring trajectory resources in a heterogeneous wireless network of unmanned aerial vehicles provided below can refer to the limitations of the method for jointly configuring trajectory resources in a heterogeneous wireless network of unmanned aerial vehicles in the above text, and will not be repeated here.

[0180] In an exemplary embodiment, Figure 6 As shown, a device for jointly configuring trajectory resources in a heterogeneous wireless network of unmanned aerial vehicles is provided, including: an acquisition module 601 and a configuration module 602, wherein:

[0181] The acquisition module 601 is used to acquire the initial trajectory information and the initial communication resource configuration corresponding to the target UAV, and determine the initial energy efficiency corresponding to the target UAV according to the initial trajectory information and the initial communication resource configuration;

[0182] The configuration module 602 is used to determine the intermediate trajectory information and the intermediate communication resource configuration according to the initial trajectory information, the initial communication resource configuration and the inner loop model; determine the intermediate energy efficiency according to the intermediate trajectory information, the intermediate communication resource configuration and the outer loop model; and the first iteration termination unit is used to determine whether the first iterative optimization process is terminated according to the intermediate energy efficiency, and if the first iterative optimization process is terminated, determine the intermediate trajectory information and the intermediate communication resource configuration as the running configuration data.

[0183] In one embodiment, the configuration module 602 includes:

[0184] The first iteration unfinished unit is used to continue the first iteration optimization processing of the intermediate trajectory information, the intermediate communication resource configuration and the intermediate energy efficiency according to the UAV configuration model if the first iteration optimization processing process has not been completed until the operation configuration data is obtained.

[0185] In one embodiment, the inner loop unit is specifically used to perform:

[0186] The inner loop model is used to perform a second iterative optimization process on the initial communication resource configuration and the inner loop model to obtain the intermediate trajectory information and the intermediate communication resource configuration.

[0187] In one embodiment, the inner loop unit is further configured to execute:

[0188] Optimizing the initial trajectory information and the initial communication resource configuration according to the inner loop model to obtain optimized trajectory information and optimized communication resource configuration;

[0189] Determining whether the second iterative optimization process is completed according to the optimized trajectory information and the optimized communication resource configuration;

[0190] If the second iterative optimization process is finished, the optimized trajectory information is used as the intermediate trajectory information, and the optimized communication resource configuration is used as the intermediate communication resource configuration;

[0191] If the second iterative optimization process is not finished, the optimized trajectory information and the optimized communication resource configuration are continuously optimized according to the inner loop model until the intermediate communication resource configuration is obtained.

[0192] In one embodiment, the initial communication resource configuration includes an initial user scheduling configuration, an initial transmission power configuration, and an initial transmission bandwidth configuration, and the inner loop unit is specifically used to perform:

[0193] Obtaining an optimized user scheduling configuration according to the first sub-problem model included in the inner loop model, the initial trajectory information, the initial transmission power configuration, and the initial transmission bandwidth configuration;

[0194] Obtaining the optimized trajectory information according to the second sub-problem model included in the inner loop model, the optimized user scheduling configuration, the initial transmission power configuration, and the initial transmission bandwidth configuration;

[0195] Obtaining an optimized transmission bandwidth configuration according to the third sub-problem model included in the inner loop model, the optimized user scheduling configuration, the optimized trajectory information, and the initial transmission power configuration;

[0196] An optimized transmission power configuration is obtained according to the fourth sub-problem model included in the inner loop model, the optimized user scheduling configuration, the optimized trajectory information and the optimized transmission bandwidth configuration.

[0197] In one embodiment, the user scheduling configuration represents users who are in communication connection with the target drone within a preset time period, and the users include real-time users and non-real-time users. The real-time users are users who maintain communication connection with the target drone, and the non-real-time users are users who maintain communication connection with the target drone within a preset time slot.

[0198] Each module in the above-mentioned device for jointly configuring trajectory resources in a heterogeneous wireless network of unmanned aerial vehicles can be implemented in whole or in part by software, hardware, or a combination thereof. Each of the above-mentioned modules can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a memory in a computer device in the form of software, so that the processor can call and execute operations corresponding to each of the above modules.

[0199] In an exemplary embodiment, a computer device is provided, which may be a target drone, and its internal structure diagram may be as shown in FIG. Figure 7 As shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, referred to as I / O) and a communication interface. Among them, the processor, the memory and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store drone configuration data. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a method for jointly configuring trajectory resources in a heterogeneous wireless network of drones is implemented.

[0200] Those skilled in the art will understand that Figure 7 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0201] In an exemplary embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the computer program, the following steps are implemented:

[0202] Acquire initial trajectory information and initial communication resource configuration corresponding to the target UAV, and determine the initial energy efficiency corresponding to the target UAV according to the initial trajectory information and the initial communication resource configuration;

[0203] Determine intermediate trajectory information and intermediate communication resource configuration according to the initial trajectory information, the initial communication resource configuration, and an inner loop model included in the drone configuration model;

[0204] Determine intermediate energy efficiency according to the intermediate trajectory information, the intermediate communication resource configuration, and an outer loop model included in the drone configuration model;

[0205] determining whether the first iterative optimization process is finished according to the intermediate energy efficiency, and if the first iterative optimization process is finished, determining the intermediate trajectory information and the intermediate communication resource configuration as operation configuration data;

[0206] The UAV configuration model is used to optimize the initial trajectory information and the initial communication resource configuration according to the initial energy efficiency.

[0207] In one embodiment, the drone configuration model includes an inner loop model and an outer loop model, and the processor further implements the following steps when executing the computer program:

[0208] Determine intermediate trajectory information and intermediate communication resource configuration according to the initial trajectory information, the initial communication resource configuration and the inner loop model; determine intermediate energy efficiency according to the intermediate trajectory information, the intermediate communication resource configuration and the outer loop model; determine whether the first iterative optimization processing process is completed according to the intermediate energy efficiency, and if the first iterative optimization processing process is completed, determine the intermediate trajectory information and the intermediate communication resource configuration as the operation configuration data.

[0209] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0210] If the first iterative optimization process is not completed, the first iterative optimization process is continued on the intermediate trajectory information, the intermediate communication resource configuration and the intermediate energy efficiency according to the UAV configuration model until the operation configuration data is obtained.

[0211] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0212] The inner loop model is used to perform a second iterative optimization process on the initial communication resource configuration and the inner loop model to obtain the intermediate trajectory information and the intermediate communication resource configuration.

[0213] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0214] The initial trajectory information and the initial communication resource configuration are optimized according to the inner loop model to obtain optimized trajectory information and optimized communication resource configuration; according to the optimized trajectory information and the optimized communication resource configuration, it is determined whether the second iterative optimization process is completed; if the second iterative optimization process is completed, the optimized trajectory information is used as the intermediate trajectory information, and the optimized communication resource configuration is used as the intermediate communication resource configuration; if the second iterative optimization process is not completed, the optimized trajectory information and the optimized communication resource configuration are continuously optimized according to the inner loop model until the intermediate communication resource configuration is obtained.

[0215] In one embodiment, the initial communication resource configuration includes an initial user scheduling configuration, an initial transmission power configuration, and an initial transmission bandwidth configuration, and the processor further implements the following steps when executing the computer program:

[0216] According to the first sub-problem model included in the inner loop model, the initial trajectory information, the initial transmission power configuration and the initial transmission bandwidth configuration, an optimized user scheduling configuration is obtained; according to the second sub-problem model included in the inner loop model, the optimized user scheduling configuration, the initial transmission power configuration and the initial transmission bandwidth configuration, the optimized trajectory information is obtained; according to the third sub-problem model included in the inner loop model, the optimized user scheduling configuration, the optimized trajectory information and the initial transmission power configuration, an optimized transmission bandwidth configuration is obtained; according to the fourth sub-problem model included in the inner loop model, the optimized user scheduling configuration, the optimized trajectory information and the optimized transmission bandwidth configuration, an optimized transmission power configuration is obtained.

[0217] In one embodiment, the user scheduling configuration represents users who are in communication connection with the target drone within a preset time period, and the users include real-time users and non-real-time users. The real-time users are users who maintain communication connection with the target drone, and the non-real-time users are users who maintain communication connection with the target drone within a preset time slot.

[0218] In one embodiment, a computer readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented:

[0219] Acquire initial trajectory information and initial communication resource configuration corresponding to the target UAV, and determine the initial energy efficiency corresponding to the target UAV according to the initial trajectory information and the initial communication resource configuration;

[0220] Determine intermediate trajectory information and intermediate communication resource configuration according to the initial trajectory information, the initial communication resource configuration, and an inner loop model included in the drone configuration model;

[0221] Determine intermediate energy efficiency according to the intermediate trajectory information, the intermediate communication resource configuration, and an outer loop model included in the drone configuration model;

[0222] determining whether the first iterative optimization process is finished according to the intermediate energy efficiency, and if the first iterative optimization process is finished, determining the intermediate trajectory information and the intermediate communication resource configuration as operation configuration data;

[0223] The UAV configuration model is used to optimize the initial trajectory information and the initial communication resource configuration according to the initial energy efficiency.

[0224] In one embodiment, the drone configuration model includes an inner loop model and an outer loop model, and when the computer program is executed by the processor, the following steps are also implemented:

[0225] Determining intermediate trajectory information and intermediate communication resource configuration according to the initial trajectory information, the initial communication resource configuration and the inner loop model;

[0226] determining an intermediate energy efficiency according to the intermediate trajectory information, the intermediate communication resource configuration, and the outer loop model;

[0227] Determine whether the first iterative optimization process is finished according to the intermediate energy efficiency; if the first iterative optimization process is finished, determine the intermediate trajectory information and the intermediate communication resource configuration as the operation configuration data.

[0228] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0229] If the first iterative optimization process is not completed, the first iterative optimization process is continued on the intermediate trajectory information, the intermediate communication resource configuration and the intermediate energy efficiency according to the UAV configuration model until the operation configuration data is obtained.

[0230] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0231] The inner loop model is used to perform a second iterative optimization process on the initial communication resource configuration and the inner loop model to obtain the intermediate trajectory information and the intermediate communication resource configuration.

[0232] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0233] Optimizing the initial trajectory information and the initial communication resource configuration according to the inner loop model to obtain optimized trajectory information and optimized communication resource configuration;

[0234] Determining whether the second iterative optimization process is completed according to the optimized trajectory information and the optimized communication resource configuration;

[0235] If the second iterative optimization process is finished, the optimized trajectory information is used as the intermediate trajectory information, and the optimized communication resource configuration is used as the intermediate communication resource configuration;

[0236] If the second iterative optimization process is not finished, the optimized trajectory information and the optimized communication resource configuration are continuously optimized according to the inner loop model until the intermediate communication resource configuration is obtained.

[0237] In one embodiment, the initial communication resource configuration includes an initial user scheduling configuration, an initial transmission power configuration, and an initial transmission bandwidth configuration, and the computer program, when executed by a processor, further implements the following steps:

[0238] Obtaining an optimized user scheduling configuration according to the first sub-problem model included in the inner loop model, the initial trajectory information, the initial transmission power configuration, and the initial transmission bandwidth configuration;

[0239] Obtaining the optimized trajectory information according to the second sub-problem model included in the inner loop model, the optimized user scheduling configuration, the initial transmission power configuration, and the initial transmission bandwidth configuration;

[0240] Obtaining an optimized transmission bandwidth configuration according to the third sub-problem model included in the inner loop model, the optimized user scheduling configuration, the optimized trajectory information, and the initial transmission power configuration;

[0241] An optimized transmission power configuration is obtained according to the fourth sub-problem model included in the inner loop model, the optimized user scheduling configuration, the optimized trajectory information and the optimized transmission bandwidth configuration.

[0242] In one embodiment, the user scheduling configuration represents users who are in communication connection with the target drone within a preset time period, and the users include real-time users and non-real-time users. The real-time users are users who maintain communication connection with the target drone, and the non-real-time users are users who maintain communication connection with the target drone within a preset time slot.

[0243] In one embodiment, a computer program product is provided, comprising a computer program, which, when executed by a processor, implements the following steps:

[0244] Acquire initial trajectory information and initial communication resource configuration corresponding to the target UAV, and determine the initial energy efficiency corresponding to the target UAV according to the initial trajectory information and the initial communication resource configuration;

[0245] Determine intermediate trajectory information and intermediate communication resource configuration according to the initial trajectory information, the initial communication resource configuration, and an inner loop model included in the drone configuration model;

[0246] Determine intermediate energy efficiency according to the intermediate trajectory information, the intermediate communication resource configuration, and an outer loop model included in the drone configuration model;

[0247] determining whether the first iterative optimization process is finished according to the intermediate energy efficiency, and if the first iterative optimization process is finished, determining the intermediate trajectory information and the intermediate communication resource configuration as operation configuration data;

[0248] The UAV configuration model is used to optimize the initial trajectory information and the initial communication resource configuration according to the initial energy efficiency.

[0249] In one embodiment, the drone configuration model includes an inner loop model and an outer loop model, and when the computer program is executed by the processor, the following steps are also implemented:

[0250] Determining intermediate trajectory information and intermediate communication resource configuration according to the initial trajectory information, the initial communication resource configuration and the inner loop model;

[0251] determining an intermediate energy efficiency according to the intermediate trajectory information, the intermediate communication resource configuration, and the outer loop model;

[0252] Determine whether the first iterative optimization process is finished according to the intermediate energy efficiency; if the first iterative optimization process is finished, determine the intermediate trajectory information and the intermediate communication resource configuration as the operation configuration data.

[0253] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0254] If the first iterative optimization process is not completed, the first iterative optimization process is continued on the intermediate trajectory information, the intermediate communication resource configuration and the intermediate energy efficiency according to the UAV configuration model until the operation configuration data is obtained.

[0255] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0256] The inner loop model is used to perform a second iterative optimization process on the initial communication resource configuration and the inner loop model to obtain the intermediate trajectory information and the intermediate communication resource configuration.

[0257] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0258] Optimizing the initial trajectory information and the initial communication resource configuration according to the inner loop model to obtain optimized trajectory information and optimized communication resource configuration;

[0259] Determining whether the second iterative optimization process is completed according to the optimized trajectory information and the optimized communication resource configuration;

[0260] If the second iterative optimization process is finished, the optimized trajectory information is used as the intermediate trajectory information, and the optimized communication resource configuration is used as the intermediate communication resource configuration;

[0261] If the second iterative optimization process is not finished, the optimized trajectory information and the optimized communication resource configuration are continuously optimized according to the inner loop model until the intermediate communication resource configuration is obtained.

[0262] In one embodiment, the initial communication resource configuration includes an initial user scheduling configuration, an initial transmission power configuration, and an initial transmission bandwidth configuration, and the computer program, when executed by a processor, further implements the following steps:

[0263] Obtaining an optimized user scheduling configuration according to the first sub-problem model included in the inner loop model, the initial trajectory information, the initial transmission power configuration, and the initial transmission bandwidth configuration;

[0264] Obtaining the optimized trajectory information according to the second sub-problem model included in the inner loop model, the optimized user scheduling configuration, the initial transmission power configuration, and the initial transmission bandwidth configuration;

[0265] Obtaining an optimized transmission bandwidth configuration according to the third sub-problem model included in the inner loop model, the optimized user scheduling configuration, the optimized trajectory information, and the initial transmission power configuration;

[0266] An optimized transmission power configuration is obtained according to the fourth sub-problem model included in the inner loop model, the optimized user scheduling configuration, the optimized trajectory information and the optimized transmission bandwidth configuration.

[0267] In one embodiment, the user scheduling configuration represents users who are in communication connection with the target drone within a preset time period, and the users include real-time users and non-real-time users. The real-time users are users who maintain communication connection with the target drone, and the non-real-time users are users who maintain communication connection with the target drone within a preset time slot.

[0268] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0269] A person of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment method can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, an artificial intelligence (AI) processor, etc., but are not limited to this.

[0270] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0271] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A method for joint configuration of trajectory resources in a heterogeneous wireless network of unmanned aerial vehicles, characterized in that: The method comprises: Acquire initial trajectory information and initial communication resource configuration corresponding to the target UAV, and determine the initial energy efficiency corresponding to the target UAV according to the initial trajectory information and the initial communication resource configuration; Determine intermediate trajectory information and intermediate communication resource configuration according to the initial trajectory information, the initial communication resource configuration, and an inner loop model included in the drone configuration model; Determine intermediate energy efficiency according to the intermediate trajectory information, the intermediate communication resource configuration, and an outer loop model included in the drone configuration model; determining whether the first iterative optimization process is finished according to the intermediate energy efficiency, and if the first iterative optimization process is finished, determining the intermediate trajectory information and the intermediate communication resource configuration as operation configuration data; The UAV configuration model is used to optimize the initial trajectory information and the initial communication resource configuration according to the initial energy efficiency; The determining of intermediate trajectory information and intermediate communication resource configuration according to the initial trajectory information, the initial communication resource configuration, and the inner loop model included in the drone configuration model includes: The inner loop model is used to perform a second iterative optimization process on the initial communication resource configuration and the inner loop model to obtain the intermediate trajectory information and the intermediate communication resource configuration.

2. The method according to claim 1, characterized in that: The method further comprises: If the first iterative optimization process is not completed, the first iterative optimization process is continued on the intermediate trajectory information, the intermediate communication resource configuration and the intermediate energy efficiency according to the UAV configuration model until the operation configuration data is obtained.

3. The method according to claim 1, characterized in that The using the inner loop model to perform a second iterative optimization process on the initial communication resource configuration and the inner loop model to obtain the intermediate trajectory information and the intermediate communication resource configuration includes: Optimizing the initial trajectory information and the initial communication resource configuration according to the inner loop model to obtain optimized trajectory information and optimized communication resource configuration; Determining whether the second iterative optimization process is completed according to the optimized trajectory information and the optimized communication resource configuration; If the second iterative optimization process is finished, the optimized trajectory information is used as the intermediate trajectory information, and the optimized communication resource configuration is used as the intermediate communication resource configuration; If the second iterative optimization process is not finished, the optimized trajectory information and the optimized communication resource configuration are continuously optimized according to the inner loop model until the intermediate communication resource configuration is obtained.

4. The method according to claim 3, characterized in that The initial communication resource configuration includes an initial user scheduling configuration, an initial transmission power configuration, and an initial transmission bandwidth configuration, and the initial trajectory information and the initial communication resource configuration are optimized according to the inner loop model to obtain the optimized trajectory information and the optimized communication resource configuration, including: Obtaining an optimized user scheduling configuration according to the first sub-problem model included in the inner loop model, the initial trajectory information, the initial transmission power configuration, and the initial transmission bandwidth configuration; Obtaining the optimized trajectory information according to the second sub-problem model included in the inner loop model, the optimized user scheduling configuration, the initial transmission power configuration, and the initial transmission bandwidth configuration; Obtaining an optimized transmission bandwidth configuration according to the third sub-problem model included in the inner loop model, the optimized user scheduling configuration, the optimized trajectory information, and the initial transmission power configuration; An optimized transmission power configuration is obtained according to the fourth sub-problem model included in the inner loop model, the optimized user scheduling configuration, the optimized trajectory information and the optimized transmission bandwidth configuration.

5. The method according to claim 4, characterized in that The user scheduling configuration represents users that are in communication connection with the target drone within a preset time period, and the users include real-time users and non-real-time users. The real-time users are users that maintain communication connection with the target drone, and the non-real-time users are users that maintain communication connection with the target drone within a preset time slot.

6. The method according to claim 1, characterized in that The intermediate energy efficiency is used to determine an objective function value corresponding to the intermediate energy efficiency, and the objective function value corresponding to the intermediate energy efficiency is used to determine whether the first iterative optimization process is completed.

7. A device for jointly configuring trajectory resources in a heterogeneous wireless network of unmanned aerial vehicles, characterized in that: The device comprises: An acquisition module, used to acquire initial trajectory information and initial communication resource configuration corresponding to the target UAV, and determine the initial energy efficiency corresponding to the target UAV according to the initial trajectory information and the initial communication resource configuration; a configuration module, configured to determine intermediate trajectory information and intermediate communication resource configuration according to the initial trajectory information, the initial communication resource configuration, and an inner loop model included in the drone configuration model; determine intermediate energy efficiency according to the intermediate trajectory information, the intermediate communication resource configuration, and an outer loop model included in the drone configuration model; determine whether the first iterative optimization process is completed according to the intermediate energy efficiency, and if the first iterative optimization process is completed, determine the intermediate trajectory information and the intermediate communication resource configuration as running configuration data; The UAV configuration model is used to optimize the initial trajectory information and the initial communication resource configuration according to the initial energy efficiency; The inner loop unit is specifically used to execute: using the inner loop model to perform a second iterative optimization process on the initial communication resource configuration and the inner loop model to obtain the intermediate trajectory information and the intermediate communication resource configuration.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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