Method for allocating resources in a full-duplex drone relay communication system based on millimeter waves

Abstract

The application discloses a resource allocation method for a full-duplex unmanned aerial vehicle (UAV) relay communication system based on millimeter waves, which comprises the following steps: establishing a millimeter wave full-duplex UAV relay communication system model; based on the established millimeter wave full-duplex UAV relay communication system model, deducing and calculating a millimeter wave full-duplex UAV average transmission rate expression, and constructing a millimeter wave channel model; based on the millimeter wave full-duplex UAV average transmission rate expression, and in combination with the millimeter wave channel model, constructing a millimeter wave full-duplex UAV average transmission rate optimization model, so as to jointly optimize user scheduling, a UAV flight trajectory, a simulated beamforming vector and a UAV transmission power, and maximize the average transmission rate; and solving the optimization problem to obtain an optimization result. The technical scheme of the application can fully utilize the high mobility of the UAV to maximize the communication performance of the millimeter wave.

Description

Technical Field

[0001] This invention relates to the field of wireless communication technology, and in particular to a resource allocation method for a millimeter-wave-based full-duplex unmanned aerial vehicle (UAV) relay communication system. Background Technology

[0002] In recent years, the application of drones in earthquake relief, emergency communications, and express delivery has attracted widespread attention. Many countries around the world are accelerating research into drone applications, with drone-assisted communication being a key area. Thanks to their high mobility, drones can be flexibly deployed in environments with poor communication conditions, such as deserts, remote rural areas, and disaster areas where base stations have been damaged. As relay base stations, drones can easily establish Line of Service (LOS) links, providing reliable communication services from the air to ground users and expanding coverage, effectively improving communication quality in harsh environments. With the promotion of fifth-generation wireless communication technology and the widespread adoption of applications such as autonomous driving, telemedicine, and ultra-high-definition video, massive data demands have arisen. Traditional mobile communication networks mostly use low-frequency bands below 6GHz, with typical bandwidths between 20MHz and 100MHz, which are insufficient to meet the needs of these emerging services. To address the shortage of spectrum resources, developing and utilizing higher-frequency millimeter-wave bands has become a necessary research topic. Full-duplex communication allows both the sender and receiver to transmit and receive electromagnetic signals simultaneously on the same frequency band at the same time, significantly improving spectrum efficiency.

[0003] Combining technologies such as drones, millimeter waves, and full-duplex technology holds great promise for future development. Drones, with their flexibility and high maneuverability, can easily reach ground users with poor communication conditions and establish line-of-sight links. Millimeter waves, with their abundant spectrum resources, can alleviate the current spectrum shortage and provide higher capacity and speed for communication networks. Full-duplex technology can improve spectrum efficiency, making it possible to further increase network capacity.

[0004] However, existing research combining these three technologies is limited, with most studies only investigating combinations of two. While some studies involve all three, they only consider single-user scenarios and fail to account for the impact of UAV flight trajectories on communication performance. Some studies also lack comprehensive consideration of self-interference cancellation in full-duplex technology. Furthermore, corresponding resource optimization schemes for UAV relay communication systems are also lacking. Summary of the Invention

[0005] This invention provides a resource allocation method for a millimeter-wave-based full-duplex UAV relay communication system, addressing the technical problem of the lack of corresponding solutions for resource optimization in existing UAV relay communication systems. It fully utilizes the high maneuverability of UAVs to maximize the communication performance of millimeter waves.

[0006] To solve the above-mentioned technical problems, the present invention provides the following technical solution:

[0007] On one hand, the present invention provides a resource allocation method for a millimeter-wave-based full-duplex UAV relay communication system, the resource allocation method for the millimeter-wave-based full-duplex UAV relay communication system comprising:

[0008] A millimeter-wave full-duplex UAV relay communication system model is established; wherein, the millimeter-wave full-duplex UAV relay communication system model includes: a ground base station, a UAV, and multiple ground users, the UAV adopts full-duplex communication and acts as a relay to provide communication services to multiple ground users; the ground base station, the UAV, and the ground users use millimeter waves as carriers for signal transmission;

[0009] Based on the established model of the millimeter-wave full-duplex UAV relay communication system, the expression for the average transmission rate of the millimeter-wave full-duplex UAV is derived and the millimeter-wave channel model is constructed.

[0010] Based on the expression for the average transmission rate of millimeter-wave full-duplex UAVs and combined with the millimeter-wave channel model, an optimization model for the average transmission rate of millimeter-wave full-duplex UAVs is constructed to jointly optimize user scheduling, UAV flight trajectory, simulated beamforming vector and UAV transmit power, so as to maximize the average transmission rate.

[0011] The optimization model for the average transmission rate of the millimeter-wave full-duplex UAV was solved, and the optimization results were obtained.

[0012] Furthermore, the establishment of the millimeter-wave full-duplex UAV relay communication system model includes:

[0013] The system acquires location information of a ground base station, a drone, and ground users. There is one ground base station, one drone, and K ground users. The drone acts as a relay, receiving signals from the ground base station simultaneously on the same frequency band and forwarding them to the ground users. The drone flies sequentially over different users at a constant altitude H along a defined flight path, serving the current user before moving on to the next. The ground base station is equipped with an antenna array M. b ×N b The UAV is equipped with a receiving antenna array M r ×N r and transmitting antenna array M t ×Nt The ground user uses a single antenna;

[0014] Based on the location information of the ground base station, the UAV, and the ground user, a millimeter-wave full-duplex UAV relay communication system model is established; wherein, a three-dimensional Cartesian coordinate system is established with the ground base station as the origin, and the coordinates of the ground base station are (0,0,h). b ), h b The altitude of the base station is given. Multiple ground users are randomly distributed within a square area with side length D. The coordinates of the k-th ground user are given by g. k =(x k ,y k ,0); Let the flight period of the UAV be T and divide it into N time slots, then the length of each time slot is δ=T / N. Assuming that the position of the UAV remains approximately unchanged in each time slot, the time-varying coordinates of the UAV in different time slots are u[n]=(q[n],H), where q[n]=[x[n],y[n]] T The horizontal coordinate is used; the K ground users are divided into K / M groups, and each group contains M users.

[0015] Furthermore, the average transmission rate is expressed as follows:

[0016]

[0017] Among them, R B2G Indicates the average transmission rate; α k [n] represents the scheduling factor. If ground user k is scheduled in time slot n, then α k [n] = 1, otherwise α k [n] = 0; M represents the number of users in each group;

[0018]

[0019]

[0020] Among them, H B2U [n] represents the channel matrix between the base station and the UAV in the nth time slot; w b [n] represents the beamforming vector of the ground base station in the nth time slot; P B Indicates the base station's transmit power; H SI [n] represents the self-interference channel matrix between the UAV transceiver antenna arrays in the nth time slot; P U [n] represents the UAV's transmit power in the nth time slot; Indicates the variance value; H represents the variance value; U2G,k[n] represents the channel matrix between the UAV and the k-th ground user in the nth time slot; w t,k [n] represents the beamforming vector transmitted by the UAV to the k-th ground user in the nth time slot; H B2G,k [n] represents the scattering channel matrix between the ground base station and the k-th ground user in the nth time slot; α j [n] indicates whether user j is scheduled in time slot n; H U2G,j [n] represents the channel matrix between the UAV and the j-th ground user in the n-th time slot; This represents the received beamforming vector of the UAV in the nth time slot; w t,j [n] represents the beamforming vector transmitted by the UAV to the j-th ground user in the n-th time slot.

[0021] Furthermore, the construction of the millimeter-wave channel model includes:

[0022] Considering the directionality and sparsity of millimeter-wave channels, the millimeter-wave channel matrix for different links is represented as follows:

[0023]

[0024]

[0025]

[0026]

[0027] Among them, H B2U H represents the channel matrix from the base station to the drone; U2G H represents the channel matrix from the drone to the ground user; B2G L represents the scattering channel matrix from the base station to the ground user; B2U L U2G and L B2G Let l and f represent the total number of paths for each link, where l = 1 represents line-of-sight paths and l > 1 represents non-line-of-sight paths; c represents the speed of light; f represents the speed of light. c Indicates the frequency of the carrier wave; d B2U d U2G and d B2G The distance between each link is represented by α, and the path loss coefficient is represented by r. m,n λ represents the distance between the m-th transmitting antenna element and the n-th receiving antenna element of the UAV; λ represents the wavelength of the millimeter wave. This represents the steering vector at the UAV receiving antenna array along the l-th path. These represent the elevation and azimuth angles at the UAV receiving antenna array along the l-th path, respectively. This represents the steering vector at the ground base station's transmitting antenna array along the l-th path. These represent the elevation and azimuth angles at the ground base station's transmitting antenna array along the l-th path, respectively. This represents the steering vector at the UAV's transmitting antenna array along the l-th path. These represent the elevation and azimuth angles at the UAV's transmitting antenna array, respectively; [H SI ] m,n This represents the element between the m-th transmitting antenna and the n-th receiving antenna in the self-interference channel matrix.

[0028] Furthermore, the average transmission rate optimization model for the millimeter-wave full-duplex UAV is expressed as follows:

[0029]

[0030]

[0031]

[0032]

[0033] (q[1],H)=(q0,H),

[0034] (q[N+1],H)=(q F ,H),

[0035]

[0036]

[0037] Where A represents user scheduling, Q represents flight trajectory, and w r This represents the beamforming vector at the UAV's receiving antenna; w t This represents the beamforming vector at the UAV's transmitting antenna; w b V represents the beamforming vector of a ground base station; max Let (q0,H) represent the maximum flight speed of the drone, and (q0,H) represent the initial position of the drone. F H) represents the destination position of the drone. This represents the constant mode constraint that the beamforming vector must satisfy. P represents the maximum transmit power of the UAV; (q[1],H) represents the position coordinates of the UAV in the first time slot, (q[N+1],H) represents the position coordinates of the UAV in the last time slot, and P represents the position coordinates of the UAV in the last time slot. U,k [n] represents the transmission power of the UAV to the k-th ground user in the nth time slot.

[0038] Furthermore, the optimization model for the average transmission rate of the millimeter-wave full-duplex UAV is solved to obtain the optimization results, including:

[0039] The average transmission rate optimization model of the millimeter-wave full-duplex UAV is decomposed into user scheduling subproblems, flight trajectory subproblems, beamforming vector subproblems, and UAV transmit power optimization subproblems. The block coordinate descent method and continuous convex approximation algorithm are used to solve each subproblem respectively to obtain the optimization results.

[0040] Furthermore, the block coordinate descent method and the continuous convex approximation algorithm are used to solve each subproblem separately to obtain the optimized results, including:

[0041] First, optimize the user scheduling and flight trajectory sub-problems under ideal conditions;

[0042] Then, the beamforming vectors at the three locations and the UAV's transmit power are optimized respectively; under the condition of meeting the optimization threshold, the average transmission rate is maximized, while the UAV's self-interference is suppressed.

[0043] In another aspect, the present invention also provides an electronic device comprising a processor and a memory; wherein the memory stores at least one instruction, which is loaded and executed by the processor to implement the above-described method.

[0044] In another aspect, the present invention also provides a computer-readable storage medium storing at least one instruction that is loaded and executed by a processor to implement the above-described method.

[0045] The beneficial effects of the technical solution provided by this invention include at least the following:

[0046] The system resource allocation method provided by this invention constructs a millimeter-wave full-duplex UAV relay communication system model and, based on this, builds an optimization model to maximize the average transmission rate of the UAV. By jointly optimizing user scheduling, UAV flight trajectory, beamforming vector, and UAV transmit power, the average transmission rate of the entire relay communication system is maximized. During the optimization process, self-interference between the UAV's transceiver antenna arrays is gradually reduced, and beam gain is gradually increased, thereby further improving the system's average transmission rate. This fully utilizes the high maneuverability of the UAV to maximize the communication performance of millimeter waves. Attached Figure Description

[0047] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0048] Figure 1 This is a schematic diagram of the execution flow of the resource allocation method for a full-duplex UAV relay communication system based on millimeter waves provided in an embodiment of the present invention;

[0049] Figure 2 This is a schematic diagram of a millimeter-wave full-duplex UAV relay communication system provided in an embodiment of the present invention;

[0050] Figure 3 This is a schematic diagram showing the flight cycle and average transmission rate performance of a drone under different flight trajectories. Detailed Implementation

[0051] To make the objectives, technical solutions, and advantages of the present invention clearer, the embodiments of the present invention will be described in further detail below with reference to the accompanying drawings.

[0052] First Embodiment

[0053] This embodiment provides a resource allocation method for a millimeter-wave-based full-duplex UAV relay communication system, applicable to wireless communication systems where ground user communication is limited. This method can be implemented by an electronic device, which can be a terminal or a server. The execution flow of this method is as follows: Figure 1 As shown, it includes the following steps:

[0054] S1. Establish a model of a millimeter-wave full-duplex UAV relay communication system;

[0055] Specifically, in this embodiment, a millimeter-wave full-duplex UAV relay communication system model is established by acquiring the location information of the ground base station, the UAV, and the ground user; the constructed millimeter-wave full-duplex UAV relay communication system model is as follows: Figure 2 As shown, it includes a ground base station, a full-duplex UAV, and K single-antenna ground users. The ground base station, the UAV receiving antenna, and the UAV transmitting antenna are all equipped with antenna arrays, while the ground users use single antennas. Millimeter waves are used as the carrier wave for signal transmission between the ground base station, the UAV, and the ground users. The UAV uses full-duplex communication and acts as a relay, receiving signals from the ground base station simultaneously and on the same frequency band, and forwarding them to the ground users. The UAV flies sequentially over different users at a constant altitude H along a predetermined flight path, serving the current user before moving on to the next. The ground base station is equipped with an antenna array M. b ×Nb The drone is equipped with a receiving antenna array M r ×N r and transmitting antenna array M t ×N t Ground users use a single antenna.

[0056] Furthermore, in this embodiment, a three-dimensional Cartesian coordinate system is established with the ground base station as the origin, and the coordinates of the ground base station are (0, 0, h). b ), h b The altitude of the base station is given. Ground users are randomly distributed within a square area with side length D. The coordinates of the K ground users are g. k =(x k ,y k ,0).

[0057] Furthermore, in this embodiment, the flight period of the UAV is set to T and divided into N time slots, with each time slot having a length of δ = T / N. Assuming that the position of the UAV remains approximately constant in each time slot, the time-varying coordinates of the UAV in different time slots are u[n] = (q[n], H), where q[n] = [x[n], y[n]]. T The horizontal coordinate is used; the K ground users are divided into K / M groups, and each group contains M users.

[0058] S2. Based on the established model of the millimeter-wave full-duplex UAV relay communication system, the expression for the average transmission rate of the millimeter-wave full-duplex UAV is derived and the millimeter-wave channel model is constructed.

[0059] Specifically, in this embodiment, the implementation process of S2 is as follows:

[0060] At time slot n, the signal received by the UAV from the base station is:

[0061]

[0062] Among them, P B P represents the base station's transmit power. U The s[n] represents the transmit power of the drone, and s[n] represents the transmit signal of the base station. j [n] represents the signal sent by the drone to ground user j, w r w represents the beamforming vector at the UAV receiving antenna. t H represents the beamforming vector at the UAV's transmitting antenna. B2U H represents the channel matrix from the base station to the drone. SI This represents the self-interference channel matrix between the UAV transceiver antenna arrays, where n1 represents a channel with a mean of 0 and a variance of 0. Additive white Gaussian noise;

[0063] At time slot n, the signal received by ground user k from the UAV is:

[0064]

[0065] Among them, w b H represents the beamforming vector of the ground base station. U2G H represents the channel matrix from the drone to the ground user. B2G α represents the scattering channel matrix from the base station to the ground user. k [n] represents the scheduling factor. If ground user k is scheduled in time slot n, then α k [n] = 1, otherwise α k [n] = 0, n² represents a mean of 0 and a variance of 0. Additive white Gaussian noise;

[0066] Calculate the transmission rate of the link from the base station to the UAV in time slot n:

[0067]

[0068] At time slot n, the transmission rate from the UAV to ground user k is:

[0069]

[0070] The average transmission rate from the base station to the ground user is:

[0071]

[0072] Furthermore, this embodiment constructs a millimeter-wave channel model based on the directionality and sparsity of the millimeter-wave UAV channel. The specific implementation process is as follows:

[0073] The steering vector of the antenna array is represented as:

[0074]

[0075] Where θ represents the elevation angle, φ represents the azimuth angle, d represents the distance between adjacent antennas, and λ represents the wavelength of the millimeter wave;

[0076] Considering the directionality and sparsity of millimeter-wave channels, the millimeter-wave channel matrix for different links is represented as follows:

[0077]

[0078]

[0079]

[0080]

[0081] Among them, L B2U L U2G and L B2G These represent the total number of paths for each link. When l = 1, it represents a line-of-sight path; when l > 1, it represents a non-line-of-sight path. c represents the speed of light, and f represents the speed of light. c d represents the frequency of the carrier wave. B2U d U2G and d B2G The distance between each link is represented by α, and the path loss coefficient is represented by r. m,n Let be the distance between the m-th transmitting antenna element and the n-th receiving antenna element of the UAV.

[0082] S3, based on the expression of the average transmission rate of millimeter-wave full-duplex UAVs and combined with the millimeter-wave channel model, constructs an optimization model for the average transmission rate of millimeter-wave full-duplex UAVs, in order to jointly optimize user scheduling, UAV flight trajectory, simulated beamforming vector and UAV transmit power, so as to maximize the average transmission rate.

[0083] Specifically, in this embodiment, the average transmission rate maximization optimization model is expressed as:

[0084]

[0085]

[0086]

[0087]

[0088] (q[1],H)=(q0,H),

[0089] (q[N+1],H)=(q F ,H),

[0090]

[0091]

[0092] Where A represents user scheduling, Q represents flight trajectory, and V represents flight path. max Let (q0,H) represent the maximum flight speed of the drone, and (q0,H) represent the initial position of the drone. F H) represents the destination position of the drone. This represents the constant mode constraint that the beamforming vector must satisfy. This indicates the maximum transmission power of the drone.

[0093] S4 solves the optimization model for the average transmission rate of millimeter-wave full-duplex UAVs and obtains the optimization results.

[0094] Specifically, in this embodiment, the implementation process of S4 is as follows:

[0095] The joint optimization problem is decomposed into user scheduling subproblems, flight trajectory subproblems, beamforming vector subproblems, and UAV transmit power optimization subproblems. Block coordinate descent and continuous convex approximation algorithms are used to solve each subproblem separately. Specifically, the user scheduling and flight trajectory subproblems are first optimized under ideal conditions. Then, the beamforming vectors at the three points and the UAV transmit power are optimized separately. Under the condition of satisfying the optimization threshold, the average transmission rate is maximized while suppressing self-interference of the UAV.

[0096] In summary, this embodiment utilizes a full-duplex UAV as a relay to provide communication services to multiple ground users. The ground base station, UAV receiving antenna, and UAV transmitting antenna are all equipped with antenna arrays. A three-dimensional Cartesian coordinate system is established with the ground base station as the origin. K ground users are randomly distributed within a square area with side length D. The UAV's flexibility and high maneuverability are used to establish line-of-sight links. Within a given flight cycle, the UAV serves all ground users sequentially according to the scheduling order and along an optimized trajectory. To improve the system's average transmission rate, millimeter waves are used as the carrier for signal transmission, while beamforming technology is employed to combat the high path loss of millimeter waves. The average transmission rate of the entire relay communication system is maximized through joint optimization of user scheduling, UAV flight trajectory, beamforming vector, and UAV transmitting power. During the optimization process, self-interference between the UAV's transmitting and receiving antenna arrays is gradually reduced, and beam gain is gradually increased, thereby further improving the system's average transmission rate.

[0097] Furthermore, to facilitate a better understanding of the present invention by those skilled in the art, the implementation process of the present invention will be described in detail below with a specific application example, which includes the following steps:

[0098] Step 1: Assume a millimeter-wave full-duplex UAV relay communication system has one ground base station, one UAV, and 12 ground users. The three-dimensional coordinates of the ground base station are (0, 0, 10), and the ground users are randomly distributed within a square area with a side length D = 700m. Therefore, the coordinates of the ground users are (x1, y1, 0), (x2, y2, 0), ..., (x...). 12 ,y 12 The time-varying coordinates of the UAV are (0, 0). After serving the current user, the drone flies to the vicinity of the next user to provide services. The specific steps are as follows:

[0099] 1.1) Based on the location coordinates of the ground base station and the ground user, the initial flight trajectory of the UAV is obtained. The initial trajectory of the UAV is a circle with a given center and radius, where the center is c. init =(x init ,yinit), where It is the geometric center of the ground user, and its radius is V xy It is the horizontal speed of the drone;

[0100] 1.2) Obtain the initial beamforming vector based on the initial flight trajectory.

[0101]

[0102] 1.3) Calculate the millimeter-wave channel matrix for different links:

[0103]

[0104]

[0105]

[0106]

[0107] Step 2, optimize the average transmission rate of the millimeter-wave full-duplex UAV relay communication system. Specific steps include:

[0108] 2.1) Determine the maximum transmit power P of the ground base station and the UAV. B =P U,max =20dBm, noise variance Calculate the transmission rates of B2U and U2G links under different time slots:

[0109]

[0110]

[0111] 2.2) The average transmission rate from the base station to the ground user is calculated as follows:

[0112]

[0113] 2.3) Determine the optimization threshold ε1 = 0.0001 for user scheduling and flight trajectory, and the optimization threshold ε2 = 0.0001 for beamforming vector and UAV transmit power;

[0114] 2.4) Establish an average transmission rate optimization model for millimeter-wave full-duplex UAVs, and jointly optimize user scheduling, UAV flight trajectory, beamforming vector, and UAV transmit power to maximize the average transmission rate, obtaining the optimized user scheduling A, flight trajectory Q, and beamforming vector w. τ and UAV transmission power P U The optimization results.

[0115] like Figure 3 As shown, Figure 3 This embodiment describes the relationship between the average transmission rate of the UAV relay communication system and the flight period T under three scenarios: 1) the UAV hovers over a fixed point; 2) the UAV flies along an initial circular trajectory; 3) the UAV flies along the optimal trajectory obtained by the optimization algorithm. The fixed point is the geometric center of all users. When the UAV is stationary, the average transmission rate of the UAV does not change with the flight period. This is because when the UAV is stationary, the air-to-ground channel between the UAV and the ground user remains constant. Compared with Scheme 1 and Scheme 2, the algorithm proposed in this invention achieves the highest average transmission rate. When the UAV flies along the optimal trajectory, it has sufficient time to utilize its maneuverability and establish the best air-to-ground channel conditions. This demonstrates that the method provided by this invention can effectively improve the average transmission rate of the millimeter-wave full-duplex UAV relay communication system, which has significant practical implications.

[0116] Second Embodiment

[0117] This embodiment provides an electronic device, which includes a processor and a memory; wherein the memory stores at least one instruction, which is loaded and executed by the processor to implement the method of the first embodiment.

[0118] The electronic device can vary considerably depending on its configuration or performance, and may include one or more processors (central processing units, CPUs) and one or more memories, wherein the memories store at least one instruction that is loaded by the processor and executed in accordance with the above method.

[0119] Third Embodiment

[0120] This embodiment provides a computer-readable storage medium storing at least one instruction, which is loaded and executed by a processor to implement the method of the first embodiment described above. The computer-readable storage medium may be a ROM, random access memory, CD-ROM, magnetic tape, floppy disk, or optical data storage device, etc. The instruction stored therein can be loaded and executed by a processor in a terminal.

[0121] Furthermore, it should be noted that the present invention can be provided as a method, apparatus, or computer program product. Therefore, embodiments of the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Moreover, embodiments of the present invention can take the form of a computer program product implemented on one or more computer-usable storage media containing computer-usable program code.

[0122] Embodiments of the present invention are described with reference to flowchart illustrations and / or block diagrams of methods, terminal devices (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, embedded processor, or other programmable data processing terminal device to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing terminal device, generate instructions for implementing the flowchart illustrations. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0123] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing terminal device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The functions specified in one or more boxes. These computer program instructions may also be loaded onto a computer or other programmable data processing terminal equipment to cause a series of operational steps to be performed on the computer or other programmable terminal equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable terminal equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0124] It should also be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or terminal device that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or terminal device. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or terminal device that includes said element.

[0125] Finally, it should be noted that the above description represents a preferred embodiment of the present invention. It should be pointed out that although preferred embodiments have been described, those skilled in the art, once they understand the basic inventive concept of the present invention, can make various improvements and modifications without departing from the principles described herein. These improvements and modifications should also be considered within the scope of protection of the present invention. Therefore, the appended claims are intended to be interpreted as including both the preferred embodiments and all changes and modifications falling within the scope of the embodiments of the present invention.

Claims

1. A resource allocation method for a millimeter-wave-based full-duplex unmanned aerial vehicle (UAV) relay communication system, characterized in that, The resource allocation method for the millimeter-wave-based full-duplex UAV relay communication system includes: A millimeter-wave full-duplex UAV relay communication system model is established; wherein, the millimeter-wave full-duplex UAV relay communication system model includes: a ground base station, a UAV, and multiple ground users, the UAV adopts full-duplex communication and acts as a relay to provide communication services to multiple ground users; the ground base station, the UAV, and the ground users use millimeter waves as carriers for signal transmission; Based on the established model of the millimeter-wave full-duplex UAV relay communication system, the expression for the average transmission rate of the millimeter-wave full-duplex UAV is derived and the millimeter-wave channel model is constructed. Based on the expression for the average transmission rate of millimeter-wave full-duplex UAVs and combined with the millimeter-wave channel model, an optimization model for the average transmission rate of millimeter-wave full-duplex UAVs is constructed to jointly optimize user scheduling, UAV flight trajectory, simulated beamforming vector and UAV transmit power, so as to maximize the average transmission rate. The optimization model for the average transmission rate of the millimeter-wave full-duplex UAV is solved to obtain the optimization results; The establishment of the millimeter-wave full-duplex UAV relay communication system model includes: Acquire location information of ground base stations, drones, and ground users; wherein the number of ground base stations is one, the number of drones is one, and the number of ground users is [number missing]. K One drone, acting as a relay, can receive signals from a ground base station at the same time and frequency band and forward them to ground users. The drone follows a certain flight trajectory and maintains a constant altitude. H The ground base station flies over different users in sequence, serving the current user before moving on to the next; the ground base station is equipped with an antenna array. The UAV is equipped with a receiving antenna array. and transmitting antenna array The ground user uses a single antenna; Based on the location information of ground base stations, UAVs, and ground users, a millimeter-wave full-duplex UAV relay communication system model is established; wherein, a three-dimensional Cartesian coordinate system is established with the ground base station as the origin, and the coordinates of the ground base station are... , It refers to the altitude of the base station, where multiple ground users are randomly distributed. D Within a square region with side length , the first k The coordinates of the ground users are The flight cycle of the drone is set as follows: T and divide it into N If there are 1 time slot, then the length of each time slot is 1. Assuming that the position of the UAV remains approximately constant in each time slot, the time-varying coordinates of the UAV in different time slots are: ,in Use the horizontal coordinate; K Ground users are divided into K / M There are 1 group, each containing 1 group. M One user.

2. The resource allocation method for a millimeter-wave-based full-duplex UAV relay communication system as described in claim 1, characterized in that, The average transmission rate is expressed as follows: ； in, R B2G Indicates the average transmission rate; Indicates the scheduling factor, if ground users k If it is scheduled in time slot n, then ,otherwise ; M This indicates the number of users in each group; ； ； Among them, H B2U [ n ] indicates the first n The channel matrix between the base station and the drone in each time slot; w b [ n ] indicates the first n The beamforming vector of the ground base station in each time slot; Indicates the base station's transmit power; H SI [ n ] indicates the first n The self-interference channel matrix between the UAV transceiver antenna arrays in each time slot; [ n ] indicates the first n The transmit power of the drone during each time slot; Indicates the variance value; Indicates the variance value; [ n ] indicates the first n During the first time slot, the drone and the first k Channel matrix between ground users; [ n ] indicates the first n In the first time slot, the drone... k Transmit beamforming vectors for each ground user; [ n ] indicates the first n During the first time slot, the ground base station and the first k The scattering channel matrix between ground users; [ n ] indicates user j In the time slot n Whether it is scheduled; [ n ] indicates that in the first n During the first time slot, the drone and the first j Channel matrix between ground users; Indicates the first n The received beamforming vector of the UAV in each time slot; Indicates the first n In the first time slot, the drone... j Transmit beamforming vectors for each ground user.

3. The resource allocation method for a millimeter-wave-based full-duplex UAV relay communication system as described in claim 2, characterized in that, The construction of the millimeter-wave channel model includes: Considering the directionality and sparsity of millimeter-wave channels, the millimeter-wave channel matrix for different links is represented as follows: ； ； ； ； Among them, H B2U H represents the channel matrix from the base station to the drone; U2G H represents the channel matrix from the drone to the ground user; B2G This represents the scattering channel matrix from the base station to the ground user; , and These represent the total number of paths for each link, when l = 1 indicates the line-of-sight path, when l > 1 indicates a non-line-of-sight path; c Represents the speed of light; Indicates the frequency of the carrier wave; , and Indicates the distance between each link. Indicates the path loss coefficient. For drones m The transmitting antenna element and the first n The distance between each receiving antenna element; Indicates the wavelength of a millimeter wave; Indicates the first l The path, the steering vector at the UAV receiving antenna array, They represent the first time. l The path, the elevation and azimuth angles at the UAV receiving antenna array; Indicates the first l The path, the steering vector at the ground base station's transmitting antenna array, They represent the first time. l The path, the elevation angle and azimuth angle of the ground base station transmitting antenna array; Indicates the first l The path, the steering vector at the UAV transmitting antenna array, These represent the elevation and azimuth angles at the UAV's transmitting antenna array, respectively. The first element in the self-interference channel matrix represents the... m root transmitting antenna and the first n Elements between the root receiving antennas.

4. The resource allocation method for a millimeter-wave-based full-duplex UAV relay communication system as described in claim 3, characterized in that, The average transmission rate optimization model for the millimeter-wave full-duplex UAV is expressed as follows: ； ； ； ； ； ； ； ； Where A represents user scheduling, Q represents flight trajectory, and w r This represents the beamforming vector at the UAV's receiving antenna; w t This represents the beamforming vector at the UAV's transmitting antenna; w b Represents the beamforming vector of a ground base station; This indicates the maximum flight speed of the drone. Indicates the starting position of the drone. Indicates the destination location of the drone. This represents the constant mode constraint that the beamforming vector must satisfy. Indicates the maximum transmit power of the UAV; (q[1], H ) represents the position coordinates of the UAV in the first time slot, (q[ N +1], H This indicates the position coordinates of the UAV in the last time slot. Indicates the first n In the first time slot, the drone... k Transmission power for each ground user.

5. The resource allocation method for a millimeter-wave-based full-duplex UAV relay communication system as described in claim 1, characterized in that, The optimization model for the average transmission rate of the millimeter-wave full-duplex UAV is solved to obtain the optimization results, including: The average transmission rate optimization model of the millimeter-wave full-duplex UAV is decomposed into user scheduling subproblems, flight trajectory subproblems, beamforming vector subproblems, and UAV transmit power optimization subproblems. The block coordinate descent method and continuous convex approximation algorithm are used to solve each subproblem respectively to obtain the optimization results.

6. The resource allocation method for a millimeter-wave-based full-duplex UAV relay communication system as described in claim 5, characterized in that, The block coordinate descent method and the continuous convex approximation algorithm are used to solve each subproblem separately to obtain the optimized results, including: First, optimize the user scheduling and flight trajectory sub-problems under ideal conditions; Then, the beamforming vectors at the three locations and the UAV's transmit power are optimized respectively; under the condition of meeting the optimization threshold, the average transmission rate is maximized, while the UAV's self-interference is suppressed.

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