Unmanned aerial vehicle assisted full-duplex amplification forwarding relay communication method under steady wind disturbance

Abstract

The invention discloses a full duplex amplification forwarding relay communication method assisted by an unmanned aerial vehicle under steady wind disturbance. The flight airspeed, the flight time and the flight attitude of the unmanned aerial vehicle are optimized and adjusted according to the ground track requirement and the wind speed condition of the unmanned aerial vehicle and according to the maximum and minimum airspeed limitation of the unmanned aerial vehicle for a full-duplex amplification forwarding relay communication system assisted by the fixed-wing unmanned aerial vehicle, so that the unmanned aerial vehicle flight speed, the flight time and the flight attitude of the unmanned aerial vehicle are optimized and adjusted. On the premise that flight is carried out according to a set ground track and flight airspeed limitation is met, required data forwarding services are provided for ground users, energy consumption of the unmanned aerial vehicle is reduced, and simulation experiments also show that the method can achieve a set design target.

Description

Technical Field

[0001] The present invention belongs to the technical field of wireless communications, and in particular relates to a full-duplex amplification and forwarding relay communication method assisted by a fixed-wing unmanned aerial vehicle under steady wind disturbance. Background Art

[0002] In recent years, UAV cooperative communication technology has become a hot topic in the field of wireless communication. Compared with traditional ground communication, UAV cooperative communication is easy to achieve on-demand allocation, thus having higher communication efficiency; UAVs are highly mobile, so they are more flexible and quick to deploy; the channel links between UAVs and ground terminals are mostly line-of-sight links, which can provide a better channel environment. Therefore, UAVs will play an extremely important role in the field of wireless communication in the future. Their applications mainly include: (1) as temporary base stations; (2) as mobile relays; and (3) for the Internet of Things.

[0003] At present, a large number of literatures have studied the capacity and spectrum efficiency optimization of relay communication systems when drones are used as mobile relays. In fact, drones have limited onboard energy, and energy efficiency is considered to be one of the key issues in drone communication. At present, most studies on drone relay communication consider the form of decode-and-forward relay communication, and there are few studies on drones using amplify-and-forward relay, especially full-duplex amplify-and-forward relay communication assisted by fixed-wing drones. On the other hand, wind in the natural environment, as a natural force that cannot be ignored, may affect the airspeed, ground speed and energy consumption of drones, but most of the current research on drone-assisted communication is still based on windless conditions. In an actual wind disturbance environment, when performing flight missions, drones not only have to counteract the additional resistance brought by airflow, but also need to adjust their flight attitude to resist the influence of wind speed and wind direction on flight, so that they can fly from the starting point to the end point according to the established ground trajectory. In view of this, exploring the adjustment of drone flight attitude and parameters in wind disturbance environments, as well as designing a reasonable communication resource allocation plan, are of great practical significance for improving the performance of drone relay communication. Summary of the invention

[0004] In order to address the shortcomings and deficiencies of the prior art, the purpose of the present invention is to provide a full-duplex amplification and forwarding relay communication method assisted by a fixed-wing UAV under steady wind disturbance, which provides the required data forwarding service for ground users and reduces the energy consumption of the UAV by adjusting the flight attitude, flight airspeed and time of the fixed-wing UAV relay, while flying according to a predetermined ground trajectory and complying with the flight airspeed limit.

[0005] The present invention is implemented as follows: a UAV-assisted full-duplex amplification and forwarding relay communication method under constant wind disturbance, the method comprising the following steps:

[0006] S1, when wind speed v w The component v along the x-axis wx ≥0, when the UAV acts as a relay and flies along a horizontal straight line from the source node to the destination node with the wind, the energy minimization problem of completing the data transmission task between the ground source and the destination node is solved and the optimal solution is obtained. In v wx <0, jump to step S7;

[0007] S2. When the drone acts as a relay and flies against the wind from the source node along a horizontal straight line toward the destination node, solve the energy minimization problem when completing the data transmission task between the ground source and the destination node and obtain the optimal solution.

[0008] S3, if Then, when the UAV acts as a relay and flies from the source node along a horizontal straight line toward the destination node within a given time, the optimal solution to the energy minimization problem of completing the data transmission service required by the ground source and destination nodes is U * =T * =NaN, jump to step S9;

[0009] S4. If The optimal solution for energy minimization in step S3 is Jump to step S9;

[0010] S5. If The optimal solution for energy minimization in step S3 is Jump to step S9;

[0011] S6. If The optimal solution for energy minimization in step S3 is like The optimal solution for energy minimization in step S3 is Jump to step S9;

[0012] S7. When the drone acts as a relay and flies against the wind from the source node along a horizontal straight line toward the destination node, solve the energy minimization problem when completing the data transmission task between the ground source and the destination node, and obtain the optimal solution.

[0013] S8, if The optimal solution for energy minimization in step S3 is U * =T * =NaN; otherwise, the optimal solution for energy minimization in step S3 is

[0014] S9. End.

[0015] Preferably, in step S1, the energy minimization problem when completing the data transmission task between the ground source and the destination node is expressed as:

[0016]

[0017] Us min ≤U≤U max (9b)

[0018]

[0019] in, and They represent the optimal solution of the UAV's airspeed U and the time T to complete the data forwarding task, E n (U) represents the power consumption of the UAV when it flies at an airspeed U, U min and U max are the minimum and maximum airspeed limits of the drone, v wx 、v wy and v wz The wind speed v w The components in the x, y and z axes, Q is the ground source node N 1 Need to be sent to the ground destination node N 2 The amount of data, Q lb is the ground destination node N 2 The lower limit of the amount of data that can be received per unit time, l 12 is the ground source node N 1 With the ground destination node N 2 The distance between

[0020] In the present invention, the solution of problems (9a) to (9e) includes the following steps:

[0021] (1) When v wx ≥0 and Established, at this time, the constraints (9b) and (9c) cannot be established at the same time, so problem (9) is infeasible, that is, the solution is NaN;

[0022] (2) When v wx ≥0 and Established, at this time, the constraint conditions (9b) and (9c) can be combined into First, ignore the constraints (9d) and (9e), so that the solution can be obtained through Lemma 2, which can be expressed as Next, T = Q / Q lb Substitute into equation (9e) and replace U in equation (9e) with U o Instead, at this time, if equation (9e) holds, the optimal solution to problem (9) is Otherwise, change the inequality constraint (9e) into an equality constraint and Consider it as an equation of U, and solve it to get the solution of U, denoted as U 11 , which can be written as Next, using Lemma 2, we can obtain the solution to problem (9), which can be expressed as

[0023] (3) When v wx ≥0 and Established, at this time, the constraint conditions (9b) and (9c) can be combined into U min ≤U≤U max ; First, using Lemma 2, we can get the solution U o =OP(U min ,U max ), then, T = Q / Q lb Substitute into equation (9e) and replace U in equation (9e) with U o Instead, in this case, equation (9e) holds true, and the optimal solution to problem (9) is Otherwise, the optimal solution needs to be calculated based on the following two cases:

[0024] 1) If Established, using Lemma 2, we can get the optimal solution of problem (9)

[0025] 2) If It does not hold, and problem (9) is infeasible, that is, the solution is NaN.

[0026] Preferably, in step S2, the energy minimization problem when completing the data transmission task between the ground source and the destination node is expressed as:

[0027]

[0028] Us min ≤U≤U max (10b)

[0029]

[0030]

[0031] in, and They represent the optimal solution of the UAV's airspeed U and the time T to complete the data forwarding task, E n (U) represents the power consumption of the UAV when it flies at an airspeed U, U min and U max are the minimum and maximum airspeed limits of the drone, v w is the wind speed, vwx 、v wy and v wz The wind speed v w The components in the x, y and z axes, Q is the ground source node N 1 Need to be sent to the ground destination node N 2 The amount of data, Q lb is the ground destination node N 2 The lower limit of the amount of data that can be received per unit time, l 12 is the ground source node N 1 With the ground destination node N 2 The distance between

[0032] The solutions to problems (10a) to (10e) include the following steps:

[0033] (1) When v wx ≥0 and Established, at this time, the constraints (10b) and (10c) cannot be established at the same time, so problem (10) is infeasible, that is, the solution is NaN;

[0034] (2) When v wx ≥0, and U max <v w Established, at this time, the constraint conditions (10b) and (10c) can be combined into First, ignore the constraints (10d) and (10e), and use Lemma 2 to obtain the solution Next, T = Q / Q lb Substitute into equation (10e) and replace U in equation (10e) with U o Instead, at this time, if equation (10e) holds, the optimal solution to problem (10) is Otherwise, the optimal solution needs to be calculated based on the following two cases:

[0035] 1) If If it holds, then the optimal solution to problem (10) is

[0036] 2) If If it does not hold, then problem (10) is infeasible, that is, the solution is NaN;

[0037] (3) When v wx ≥0, and U max ≥v w Established, at this time, the constraint conditions (10b) and (10c) can be combined into First, ignore the constraints (10d) and (10e), and use Lemma 2 to obtain the solution Next, T = Q / Q lb Substitute into equation (10e) and replace U in equation (10e) with U o Instead, at this time, if equation (10e) holds, the optimal solution to problem (10) is Otherwise, the optimal solution needs to be calculated based on the following two cases:

[0038] 1) If If holds, then the optimal solution to problem (10) is

[0039] 2) If It does not hold, problem (10) is infeasible, that is, the solution is NaN;

[0040] (4) When v wx ≥0, and U max ≤v w Established, at this time, the constraint conditions (10b) and (10c) can be combined into U min ≤U≤U max ; First, ignore the constraints (10d) and (10e), and use Lemma 2 to obtain the solution U o =OP(U min ,U max ), then, T = Q / Q lb Substitute into equation (10e) and replace U in equation (10e) with U o Instead, at this time, if equation (10e) holds, the optimal solution to problem (10) is Otherwise, the optimal solution needs to be calculated based on the following two cases:

[0041] 1) If If holds, then the optimal solution to the problem is

[0042] 2) If If it does not hold, then problem (10) is infeasible, that is, the solution is NaN;

[0043] (5) When v wx ≥0, and U min ≤v w ≤U max Established, at this time, the constraint conditions (10b) and (10c) can be combined into U min ≤U≤v w ; First, ignore the constraints (10d) and (10e), and use Lemma 2 to obtain the solution U o =OP(U min ,v w ), then, T = Q / Qlb Substitute into equation (10e) and replace U in equation (10e) with U o Instead, at this time, if equation (10e) holds, the optimal solution to problem (10) is Otherwise, the optimal solution needs to be calculated based on the following two cases:

[0044] 1) If If holds, then the optimal solution to problem (10) is

[0045] 2) If If it does not hold, then problem (10) is infeasible, that is, the solution is NaN;

[0046] (6) When v wx ≥0 and U min >v w Established, at this time, the constraints (10b) and (10c) cannot be satisfied at the same time, so problem (10) is infeasible, that is, the solution is NaN.

[0047] Preferably, in step S7, the energy minimization problem when completing the data transmission task between the ground source and the destination node is expressed as:

[0048]

[0049] Us min ≤U≤U max (11b)

[0050] U≥v w (11c)

[0051]

[0052] in, and They represent the optimal solution of the UAV’s airspeed U and the time T to complete the data forwarding task, En(U) represents the power consumption of the UAV when it flies at an airspeed U, and U min and U max are the minimum and maximum airspeed limits of the drone, v w is the wind speed, v wx 、v wy and v wz The wind speed v w The components in the x, y and z axes, Q is the ground source node N 1 Need to be sent to the ground destination node N 2 The amount of data, Q lb is the ground destination node N 2 The lower limit of the amount of data that can be received per unit time, l 12 is the ground source node N1 With the ground destination node N 2 The distance between

[0053] The solutions to the problems (11a) to (11e) include the following steps:

[0054] (1) When v wx <0 and U max <v w Established, at this time, the constraints (11b) and (11c) cannot be satisfied at the same time, and problem (11) is infeasible, that is, the solution is NaN;

[0055] (2) When v wx <0 and U min <v w ≤U max holds true. At this time, the constraint conditions (11b) and (11c) can be combined into v w ≤U≤U max ; First, ignore the constraints (11d) and (11e), and use Lemma 2 to obtain the solution U o =OP(v w ,U max ), then, T = Q / Q lb Substitute into equation (11e) and replace U in equation (11e) with U o Instead, at this time, if equation (11e) holds, the optimal solution to problem (11) is Otherwise, the optimal solution needs to be calculated based on the following two cases:

[0056] 1) If The optimal solution to problem (11) is

[0057] 2) If If it does not hold, then problem (11) is infeasible, that is, the solution is NaN;

[0058] (3) When v wx <0 and U min ≥v w Established, at this time, the constraint conditions (11b) and (11c) can be combined into U min ≤U≤U max ; First, ignore the constraints (11d) and (11e), and use Lemma 2 to obtain the solution U o =OP(U min ,U max ), then, T = Q / Q lb Substitute into equation (11e) and replace U in equation (11e) with U oInstead, at this time, if equation (11e) holds, the optimal solution to problem (11) is Otherwise, the optimal solution needs to be calculated based on the following two cases:

[0059] 1) If If holds, then the optimal solution to problem (11) is

[0060] 2) If It does not hold, and problem (11) is infeasible, that is, the solution is NaN.

[0061] Compared with the shortcomings and deficiencies of the prior art, the present invention has the following beneficial effects: the present invention is directed to a full-duplex amplification and forwarding relay communication system assisted by a fixed-wing UAV, and optimizes and adjusts the flight airspeed, flight time and flight attitude of the UAV according to the ground trajectory requirements of the UAV and the maximum and minimum airspeed limits of the UAV. On the premise of flying according to the established ground trajectory and complying with the flight airspeed limit, the present invention provides the required data forwarding service for ground users and reduces the energy consumption of the UAV. Simulation experiments also show that the present invention can achieve the established design goals. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] Figure 1 It is a schematic diagram of basic conditions and a schematic diagram of wind triangle of a full-duplex amplification and forwarding relay communication system assisted by a fixed-wing UAV in the present invention;

[0063] Figure 2 The energy consumption of the UAV under different data forwarding requirements;

[0064] Figure 3 The actual amount of data received by the ground destination node under different data forwarding requirements;

[0065] Figure 4 is the energy consumption of the UAV under different vertical wind speed angles;

[0066] Figure 5 The yaw angle and elevation angle of the UAV under different vertical wind speed angles;

[0067] Figure 6 are the airspeed and ground speed of the UAV at different vertical wind speed angles;

[0068] Figure 7 The actual amount of data received by the ground destination node under different vertical wind speed angles;

[0069] Figure 8 is the energy consumption of the UAV under different horizontal wind speed angles;

[0070] Fig. 9The yaw angle and elevation angle of the UAV under different horizontal wind speed angles;

[0071] Fig.10 are the airspeed and ground speed of the UAV under different horizontal wind speed angles;

[0072] Fig.11 It is the actual amount of data received by the ground destination node under different horizontal wind speed angles. DETAILED DESCRIPTION

[0073] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention 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 invention and are not intended to limit the present invention.

[0074] UAV-assisted amplification and forwarding relay communication technology under constant wind disturbance, such as Figure 1 As shown, the source node N on the ground 1 The data with a data volume of Q needs to be sent to the destination node N 2 , assuming N 1 Located at the origin, its coordinates are (0,0,0), N 2 The coordinates of the 12 ,0,0),l 12 N 1 and N 2 The distance between 1 and N 2 The distance is far, and there is no direct link. It is necessary to forward data with the help of a fixed-wing drone relay R flying at an altitude of h. The fixed-wing drone relay R always flies at an altitude of h, and its initial position is q. 0 =(0,0,h), the drone flies from the initial position to q along a straight line F =(l 12 ,0,h), the airspeed vector of the UAV relay R is U, and the ground speed vector is V g Assume that the wind speed vector of the steady wind is V w UAV R receives N during flight 1 Send the signal to the destination node N 2 Forward data. The drone receives signals and forwards data simultaneously on the same frequency band, that is, it works in full-duplex mode, and the relay forwarding adopts the Amplify-and-Forward (AF) relay protocol. Assume that the drone R starts from the initial position q 0 =(0,0,h) starts to provide data forwarding service, and the time it takes to forward data with a data volume of Q is T.

[0075] For ease of analysis, let the magnitude of the UAV ground speed vector be v g (hereinafter referred to as v g is the “ground speed”), that is, v g =||v g ||. Thus, at time t, the position of the drone is q R =(v g t,0,h). Since the drone R flies along a straight trajectory on the ground, and acts as a full-duplex amplification and forwarding relay to provide data forwarding services for ground nodes (connecting the ground source node N 1 The data is forwarded to the ground destination node N 2 ), so that the local source node N 1 and the drone relay R and the drone relay R and the ground destination node N 2 When there is a line-of-sight link between the ground destination node N 2 The actual amount of received data at time t has a lower bound, specifically Q lb t, where

[0076]

[0077] In formula (1), Q lb is the ground destination node N 2 The lower limit of the amount of data that can be received per unit time, e is a natural constant, β 0 Indicates the reference value of channel gain at a distance of 1m, P 1 and P R Represents the ground source node N 1 and the transmission power of the drone relay R, σ 2 is the noise power, l 12 N 1 and N 2 The distance between them, h is the flight altitude of the UAV relay R.

[0078] In fact, the ground speed vector, air speed vector and wind speed vector of the drone satisfy the wind triangle relationship, that is, V g =U+V w For the convenience of analysis, let the magnitude of the airspeed vector be U (hereinafter referred to as "airspeed"), that is, U = ||U||; let the magnitude of the wind speed vector be v w (hereinafter referred to as v w is the wind speed), that is, v w =||v w ||. Set the wind speed v w Decomposing along the three orthogonal directions of the three-dimensional coordinate system (i.e., the x-axis, y-axis, and z-axis directions), the wind speed v can be obtained: w The components in three orthogonal directions are v wx 、vwy and v wz In this way, there is Let θ z is the vertical wind speed angle, that is, the wind speed vector V w The angle between the horizontal plane and the x is the horizontal wind speed angle, that is, the wind speed vector V w The angle between the projection on the horizontal plane and the x-axis. Assume that -90°<θ z <90°、0°≤θ x ≤360°; if v wy ≥0, then If v wy <0, then θ z =arctan(v wz / ||v w ||). It should be noted that: when 0°≤θ x <90°or 270°<θ x ≤360°, the drone relay R will fly with the wind; when 90°<θ x When θ < 270°, the drone relay R will fly against the wind; z When θ>0°, the drone relay R will be subjected to downward wind pressure; z When <0°, the drone relay R will be subjected to upward wind pressure.

[0079] In order for the drone relay R to fly along the predetermined ground track, the drone relay R needs to adjust the yaw angle φ and the elevation angle α. Here, the yaw angle φ is defined as: the angle between the projection of the drone's airspeed vector U on the horizontal plane and the x-axis; the elevation angle α is the angle between the drone's fuselage direction and the horizontal plane. Assume that 0≤φ≤360°, -90°<α<90°; if v wy ≥0, then the yaw angle If v wy <0, then the yaw angle Elevation angle α = arcsin(v wz / ||U||). The angle of attack of the drone is omitted here, so the airspeed vector of the drone is parallel to the direction of the drone's fuselage.

[0080] Since the drone relay R flies along a straight line at a fixed altitude, the sum of all the forces acting on the drone is 0, that is, equation (2) holds.

[0081]

[0082] In formula (2), W is the overall weight of the drone (i.e., the overall mass m of the drone multiplied by the gravitational acceleration g), L is the lift force on the drone, D is the drag force on the drone, F is the thrust force generated by the drone engine, and α is the elevation angle of the drone. The drag force D on a fixed-wing drone during flight can be calculated using formula (3).

[0083]

[0084] In formula (3), C D0 is the zero lift drag coefficient, ρ is the air density, A is the wing area, U is the airspeed vector amplitude of the UAV flight (referred to as "airspeed"), W is the overall weight of the UAV, α is the elevation angle of the UAV, e o is the wingspan efficiency, and b is the wingspan of the UAV.

[0085] For fixed-wing UAVs, the engine power consumption can be regarded as a function of the UAV airspeed U, denoted as E n (U), and E n (U) is equal to the thrust F generated by it multiplied by the airspeed U, that is, E n (U) = |F|U. Here |F| represents the absolute value of the thrust F, because the UAV engine may produce a reverse thrust, in which case the value of F will be less than 0. According to formula (2), we can get F = Wsinα + D. Then, using formula (3) and α = arcsin(v wz / ||U||), the power consumption of the UAV engine can be written as E n (U)=|P(U)|, where,

[0086]

[0087] In formula (4), W is the weight of the entire drone (i.e., the overall mass of the drone m multiplied by the gravitational acceleration g), v wz is the wind speed v w The vertical component of wind speed v w component along the z-axis), C D0 is the zero lift drag coefficient, ρ is the air density, A is the wing area, U is the airspeed vector amplitude of the UAV flight (referred to as "airspeed"), e o is the wingspan efficiency, b is the wingspan of the UAV. By observing formula (4), it can be found that the engine power consumption of the UAV is only related to the vertical component of the wind speed.

[0088] Here, the UAV is required to fly along a predetermined straight ground trajectory, provide data forwarding services to the ground nodes during the flight, and minimize the energy consumption of the UAV. Therefore, according to the system requirements and the wind triangle relationship, equation (5) needs to hold.

[0089]

[0090] In formula (5), v g is the magnitude of the UAV ground speed vector (v g Referred to as "ground speed"), v wx and v wy is the wind speed v of the drone w The horizontal wind volume (i.e., wind speed v w components along the x and y axes respectively), v wz is the wind speed v of the drone w The vertical component of wind speed v w The component along the z-axis direction), U is the airspeed vector amplitude of the UAV flight (U is referred to as “airspeed” for short).

[0091] Equation (5) can be regarded as v g In order to make the drone relay R along the path from N 1 Point to N 2 For a straight ground trajectory flight, Equation (5) must have a g Therefore, Lemma 1 gives the positive solution of (5) with respect to v g The positive solution of .

[0092] Introduction 1: In formula (5), g The positive solutions of can be divided into the following three cases.

[0093] (1) When and v wx ≥0 holds true, then, there must be a positive v in equation (5) g Solution: According to the value of the yaw angle φ, it can be further divided into two cases: 1) If 0≤φ≤90° or 270°≤φ<360°, then the positive v g The solution is:

[0094]

[0095] 2) If 90°<φ<270° holds, then the positive v g The solution is:

[0096]

[0097] It should be noted that: In formula (7), In fact, according to the wind triangle relationship, if v wx ≥0 holds, and v g According to formula (6), 0≤φ≤90° or 270°≤φ<360° must hold; if and v wx≥0 holds, and v g According to formula (7), 90°<φ<270° is definitely true.

[0098] (2) When and v wx When <0 holds true, there exists a positive v in equation (5) g The solution condition is 0≤φ≤90° or 270°≤φ<360°. At this time, v g It can be given by formula (6), and it is necessary to ensure Similarly, according to the wind triangle relationship, when and v wx <0 holds, and v g According to formula (6), 0≤φ≤90° or 270°≤φ<360° must hold.

[0099] (3) When When , there is no positive v in equation (5) g untie.

[0100] Next, according to the system requirements (drone relay R needs to follow the N 1 Point to N 2 The straight ground trajectory flight uses time T to transfer data of size Q from the ground source node N 1 Forwarded to the ground destination node N 2 , and in the process the energy consumption of the UAV is minimized), an optimization problem is established, which can be specifically given by Equations (8a), (8b), (8c) and (8d).

[0101]

[0102] Us min ≤U≤U max (8b)

[0103] QQ lb T≤0(8c)

[0104]

[0105] Problem (8), that is, the optimization problem composed of equations (8a), (8b), (8c) and (8d), T is the amount of data Q from the ground source node N 1 Forwarded to the ground destination node N 2 The time required, E n (U) is the engine power consumption of the UAV relay R, U is the airspeed vector amplitude of the UAV flight (U is referred to as “airspeed” for short), U min and U maxare the minimum and maximum airspeed limits of the drone R (determined by the minimum lift required by the drone and the structural limitations of the drone), Q lb is the ground destination node N 2 The lower bound of the amount of data received per unit time, equation (8c) ensures that the ground destination node N 2 The amount of data actually received at time T will be greater than Q. Formula (8d) indicates that the drone relay R is from the initial position q 0 =(0,0,h) and flies along the straight line on the ground, reaching the final position q F =(l 12 ,0,h) before the data forwarding task is completed. In addition, problem (8) also includes the problem of adjusting the flight attitude of the drone relay R, that is, by adjusting the airspeed, yaw angle and elevation angle of the drone, the drone can move along the direction from N 1 Point to N 2 Straight ground track flight.

[0106] By observing equations (8a) and (4), it can be found that the energy consumption of the drone relay R is a monotonically increasing function of T. Therefore, the optimal solution to problem (8) will make the inequality constraint (8c) equal, that is, T = Q / Q lb There will be an optimal solution when lb It is necessary to satisfy formula (8d). v in formula (8d) g It can be given by equation (6) or equation (7), depending on the airspeed, yaw angle and wind speed of the UAV relay R.

[0107] According to Reference 1, problem (8), i.e., the optimization problem consisting of equations (8a), (8b), (8c) and (8d), is decomposed into three sub-problems, which can be specifically divided into the following two cases.

[0108] (1) When v wx ≥0, if the ground speed v g Given by formula (6), problem (8) can be rewritten as:

[0109]

[0110] Us min ≤U≤U max (9b)

[0111]

[0112] If the ground speed v g Given by formula (7), problem (8) can be rewritten as:

[0113]

[0114] Usmin ≤U≤U max (10b)

[0115]

[0116]

[0117] (2) When v wx When <0, problem (8) can be rewritten as:

[0118]

[0119] Us min ≤U≤U max (11b)

[0120] U≥v w (11c)

[0121]

[0122] It should be noted that: when v wx When ≥0, there will be two optimization problems, and each will generate a set of solutions, namely and Therefore, the solution to problem (8) at this time will be the one of the two sets of solutions that can provide smaller energy consumption.

[0123] Next, Lemma 2 is given to solve the above three sub-problems.

[0124] Lemma 2: For the fixed UAV engine power consumption minimization problem (12), that is, the optimization problem composed of equations (12a) and (12b), which is denoted as U o =OP(U lw ,U up ), where U lw and U up are the lower and upper limits of the UAV airspeed U, respectively. o represents the optimal solution of the optimization problem, |P(U)| is the power consumption of the UAV engine, and the optimal solution U o It can be divided into the following six situations.

[0125]

[0126] st0<U lw ≤U≤U up (12b)

[0127] (1) When The optimal solution is U o =U lw .

[0128] (2) When and The optimal solution can be further divided into the following three cases: 1) If P(U lw )≥0, then the optimal solution is U o =U lw ; 2) If P(U lw )<0, and P(U up )>0, optimal solution U o For P(U)=0 at U lw ≤U≤U dw The solution of the interval can be obtained by binary search; 3) If P(U up )≤0, then the optimal solution U o =U up .

[0129] (3) When and The optimal solution can be further divided into the following six cases: 1) If The optimal solution 2) If P(U lw )<0、P(U up )<0、P(U lw )<P(U up ), then the optimal solution U o =U up ; 3) If P(U lw )<0、P(U up )<0、P(U lw )≥P(U up ), then the optimal solution U o =U lw ; 4) If P(U lw )<0、P(U up )≥0, then the optimal solution U o P(U)=0 at U lw ≤U≤U dw The solution of the interval can be obtained by binary search; 5) If P(U lw )≥0, P(U up )<0, then the optimal solution U o P(U)=0 at U lw ≤U≤U dw The solution of the interval can be obtained by binary search; 6) If P(U lw )≥0, P(U up )≥0, P(U 1 o )<0, then the optimal solution U o There are two solutions, one large and one small: a) The solution for the small value is P(U) = 0 at U lw ≤U≤U1 o The solution of the interval, b) the solution of large value is P(U)=0 in The solutions of the interval can be obtained by binary search.

[0130] (4) When and The optimal solution can be further divided into the following three cases: 1) If P(U up )≥0, then the optimal solution U o =U up ; 2) If P(U up )<0、P(U lw )≥0, then the optimal solution U o P(U)=0 at U lw ≤U≤U dw The solution in the interval can be obtained by binary search; 3) If P(U lw )≤0, then the optimal solution is U o =U lw .

[0131] (5) When and The optimal solution can be further divided into the following six cases: 1) If P(U lw )≥0,P(U up )≥0, P(U lw )≤P(U up ), then the optimal solution is U o =U lw ; 2) If P(U lw )≥0, P(U up )≥0, P(U lw )>P(U up ), then the optimal solution is U o =U up ; 3) If P(U lw )≥0, P(U up )<0, then the optimal solution U o For P(U)=0 at U lw ≤U≤U dw The solution of the interval can be obtained by binary search; 4) If P(U lw )<0、P(U up )≥0, then the optimal solution U o For P(U)=0 at U lw ≤U≤U dw The solution of the interval can be obtained by binary search; 5) If P(U lw )<0、P(U up )<0, The optimal solution is 6) If P(U lw )<0、P(U up )<0, Then the optimal solution U o There are two solutions, one large and one small: a) The solution for the small value is P(U) = 0. The solution of the interval, b) the solution of large value is P(U) = 0 in The solution of the interval can be obtained by binary search.

[0132] (6) When and The optimal solution can be further divided into the following three cases: 1) If P(U lw )≥0, then the optimal solution is U o =U lw ; 2) If P(U lw )<0、P(U up )≥0, then the optimal solution U o For P(U)=0 at U lw ≤U≤U dw The solution of the interval can be obtained by binary search; 3) If P(U up )<0, then the optimal solution is U o =U up .

[0133] here, and Given by formula (13):

[0134]

[0135] in W is the weight of the drone (i.e., the overall mass of the drone m multiplied by the acceleration of gravity g), v wz is the wind speed v of the drone w The vertical component of wind speed v w component along the z-axis), is the zero lift drag coefficient, e o is the span efficiency, A is the wing area, ρ is the air density, and b is the wingspan of the UAV.

[0136] Next, for the three sub-problems decomposed from problem (8), namely, problem (9) [the optimization problem consisting of equations (9a), (9b), (9c), (9d), and (9e)], problem (10) [the optimization problem consisting of equations (10a), (10b), (10c), (10d), and (10e)], and problem (11) [the optimization problem consisting of equations (11a), (11b), (11c), (11d), and (11e)], three methods are given to solve the three sub-problems respectively, which are used to solve the problems and find the solutions to (9), problem (10), and problem (11).

[0137] Method 1: Problem (9), that is, the solution of the optimization problem composed of equations (9a), (9b), (9c), (9d), and (9e) can be given in the following three cases.

[0138] (1) When v wz ≥0 and Established, at this time, the constraints (9b) and (9c) cannot be established at the same time, so problem (9) is infeasible, that is, the solution is NaN.

[0139] (2) When v wx ≥0 and Established, at this time, the constraint conditions (9b) and (9c) can be combined into First, ignore the constraints (9d) and (9e), so that the solution can be obtained through Lemma 2, which can be expressed as Next, T = Q / Q lb Substitute into equation (9e) and replace U in equation (9e) with U o Instead, at this time, if equation (9e) holds, the optimal solution to problem (9) is Otherwise, change the inequality constraint (9e) into an equality constraint and Consider it as an equation of U, and solve it to get the solution of U, denoted as U 11 , which can be written as Next, using Lemma 2, we can obtain the solution to problem (9), which can be expressed as

[0140] (3) When v wx ≥0 and Established, at this time, the constraint conditions (9b) and (9c) can be combined into U min ≤U≤U max First, using Lemma 2, we can get the solution U o =OP(U min ,U max ). Then, T = Q / Q lb Substitute into equation (9e) and replace U in equation (9e) with U oInstead, in this case, equation (9e) holds true, and the optimal solution to problem (9) is Otherwise, we need to calculate the optimal solution in the following two cases: 1) If Established, using Lemma 2, we can get the optimal solution of problem (9) 2) If It does not hold, and problem (9) is infeasible, that is, the solution is NaN.

[0141] It should be noted that: Using Lemma 2 in Method 1 may result in two solutions. If this situation occurs and two solutions are returned, the solution with the smaller value is selected in Method 1.

[0142] Method 2: Problem (10), that is, the solution of the optimization problem composed of equation (10a), equation (10b), equation (10c), equation (10d), and equation (10e) can be given in the following six cases.

[0143] (1) When v wx ≥0 and Established, at this time, the constraints (10b) and (10c) cannot be established at the same time, so problem (10) is infeasible, that is, the solution is NaN.

[0144] (2) When v wx ≥0, and U max <v w Established, at this time, the constraint conditions (10b) and (10c) can be combined into First, ignore the constraints (10d) and (10e), and use Lemma 2 to obtain the solution Next, T = Q / Q lb Substitute into equation (10e) and replace U in equation (10e) with U o Instead, at this time, if equation (10e) holds, the optimal solution to problem (10) is Otherwise, we need to calculate the optimal solution in the following two cases: 1) If If it holds, then the optimal solution to problem (10) is 2) If If it does not hold, then problem (10) is infeasible, that is, the solution is NaN.

[0145] (3) When v wx ≥0, and U max ≥v w Established, at this time, the constraint conditions (10b) and (10c) can be combined into First, ignore the constraints (10d) and (10e), and use Lemma 2 to obtain the solution Next, T = Q / Qlb Substitute into equation (10e) and replace U in equation (10e) with U o Instead, at this time, if equation (10e) holds, the optimal solution to problem (10) is Otherwise, we need to calculate the optimal solution in the following two cases: 1) If If it holds, then the optimal solution to problem (10) is 2) If It does not hold, and problem (10) is infeasible, that is, the solution is NaN.

[0146] (4) When v wx ≥0, and U max ≤v w Established, at this time, the constraint conditions (10b) and (10c) can be combined into U min ≤U≤U max First, ignore the constraints (10d) and (10e), and use Lemma 2 to obtain the solution U o =OP(U min ,U max ). Then, T = Q / Q lb Substitute into equation (10e) and replace U in equation (10e) with U o Instead, at this time, if equation (10e) holds, the optimal solution to problem (10) is Otherwise, we need to calculate the optimal solution in the following two cases: 1) If If holds, then the optimal solution to the problem is 2) If If it does not hold, then problem (10) is infeasible, that is, the solution is NaN.

[0147] (5) When v wx ≥0, and U min ≤v w ≤U max Established, at this time, the constraint conditions (10b) and (10c) can be combined into U min ≤U≤v w First, ignore the constraints (10d) and (10e), and use Lemma 2 to obtain the solution U o =OP(U min ,v w ). Then, T = Q / Q lb Substitute into equation (10e) and replace U in equation (10e) with U o Instead, at this time, if equation (10e) holds, the optimal solution to problem (10) is Otherwise, we need to calculate the optimal solution in the following two cases: 1) If If it holds, then the optimal solution to problem (10) is 2) If If it does not hold, then problem (10) is infeasible, that is, the solution is NaN.

[0148] (6) When v wx ≥0 and U min >v w Established, at this time, the constraints (10b) and (10c) cannot be satisfied at the same time, so problem (10) is infeasible, that is, the solution is NaN.

[0149] It should be noted that: Using Lemma 2 in Method 2 may result in two solutions. If this situation occurs and two solutions are returned, the solution with the larger value is selected in Method 2.

[0150] Method 3: Problem (11), that is, the solution of the optimization problem composed of equation (11a), equation (11b), equation (11c), equation (11d), and equation (11e) can be given in the following three cases.

[0151] (1) When v wx <0 and U max ≤v w Established, at this time, the constraints (11b) and (11c) cannot be satisfied at the same time, and problem (11) is infeasible, that is, the solution is NaN.

[0152] (2) When v wx <0 and U min <v w ≤U max holds true. At this time, the constraint conditions (11b) and (11c) can be combined into v w ≤U≤U max First, ignore the constraints (11d) and (11e), and use Lemma 2 to obtain the solution U o =OP(v w ,U max ). Then, T = Q / Q lb Substitute into equation (11e) and replace U in equation (11e) with U o Instead, at this time, if equation (11e) holds, the optimal solution to problem (11) is Otherwise, we need to calculate the optimal solution in the following two cases: 1) If The optimal solution to problem (11) is 2) If If it does not hold, then problem (11) is infeasible, that is, the solution is NaN.

[0153] (3) When v wx <0 and Umin ≥v w Established, at this time, the constraint conditions (11b) and (11c) can be combined into U min ≤U≤U max First, ignore the constraints (11d) and (11e), and use Lemma 2 to obtain the solution U o =OP(U min ,U max ). Then, T = Q / Q lb Substitute into equation (11e) and replace U in equation (11e) with U o Instead, at this time, if equation (11e) holds, the optimal solution to problem (11) is Otherwise, we need to calculate the optimal solution in the following two cases: 1) If If holds, then the optimal solution to problem (11) is 2) If It does not hold, and problem (11) is infeasible, that is, the solution is NaN.

[0154] It should be noted that: Using Lemma 2 in Method 3 may result in two solutions. If this situation occurs, the solution with the smaller value is selected in Method 3.

[0155] According to method 1, method 2 and method 3, the algorithm for solving problem (8), that is, the optimization problem composed of equation (8a), equation (8b), equation (8c) and equation (8d) is given below, as shown in Algorithm 1.

[0156] Algorithm 1: Algorithm for solving problem (8), i.e., the optimization problem composed of equations (8a), (8b), (8c) and (8d).

[0157] S1, when wind speed v w The component v along the x-axis wx ≥0, when the UAV acts as a relay and flies along a horizontal straight line from the source node to the destination node with the wind, the energy minimization problem of completing the data transmission task between the ground source and the destination node is solved and the optimal solution is obtained. In v wx <0, jump to step S7;

[0158] In step S1, specifically, if v wx ≥0 holds true, then method 1 is used to solve problem (9) and the optimal solution is obtained. If v wx If <0, jump to step 7.

[0159] S2. When the drone acts as a relay and flies against the wind from the source node along a horizontal straight line toward the destination node, solve the energy minimization problem when completing the data transmission task between the ground source and the destination node and obtain the optimal solution.

[0160] In step S2, specifically, method 2 is used to solve problem (10) and the optimal solution is obtained.

[0161] S3, if Then, when the UAV acts as a relay and flies from the source node along a horizontal straight line toward the destination node within a given time, the optimal solution to the energy minimization problem of completing the data transmission service required by the ground source and destination nodes is U * =T * =NaN, jump to step S9;

[0162] In step S3, if Then the optimal solution of problem (8) is U * =T * =NaN, then jump to step 9.

[0163] S4. If The optimal solution for energy minimization in step S3 is Jump to step S9;

[0164] In step S4, if The optimal solution to problem (8) is Then, skip to step 9.

[0165] S5. If The optimal solution for energy minimization in step S3 is Jump to step S9;

[0166] In step S5, if The optimal solution to problem (8) is Then, skip to step 9.

[0167] S6. If The optimal solution for energy minimization in step S3 is like The optimal solution for energy minimization in step S3 is Jump to step S9;

[0168] In step S6, if The optimal solution to problem (8) is like The optimal solution to problem (8) is Then, skip to step 9.

[0169] S7. When the drone acts as a relay and flies against the wind from the source node along a horizontal straight line toward the destination node, solve the energy minimization problem when completing the data transmission task between the ground source and the destination node, and obtain the optimal solution.

[0170] In step S7, specifically, method 3 is used to solve problem (11) and the optimal solution is obtained.

[0171] S8, if The optimal solution for energy minimization in step S3 is U * =T * =NaN; otherwise, the optimal solution for energy minimization in step S3 is

[0172] In step S8, if The optimal solution to problem (8) is U * =T * =NaN; otherwise, the optimal solution to problem (8) is

[0173] Step 9: The algorithm ends.

[0174] It should be noted that “NaN” in Algorithm 1 indicates a non-numerical solution, that is, problem (8) is not feasible.

[0175] A simulation experiment was conducted for the optimization method proposed in the present invention, and the experimental environment was a Matlab environment. In the experiment, the "sqp" algorithm in the Matlab optimization toolbox was used to verify the correctness of the proposed optimization method. In the experimental result graph, "simulation" is used to represent the data obtained by the "sqp" algorithm. The parameter values ​​in the experiment are shown in Table 1 below.

[0176] Table 1

[0177]

[0178] Attached Figure 2 , Figure 3 The energy consumption of the UAV and the amount of data actually received by the ground destination node under different data forwarding requirements are given respectively. It should be noted that in order to obtain the amount of data actually received by the ground destination node, the residual self-interference channel power is set to -60dB in the simulation experiment. Figure 2 It shows that the energy consumption of the drone increases with the increase of the Q value (the amount of data to be forwarded). Figure 2 It is confirmed that the energy consumption of the UAV is only related to the vertical component of the wind speed, that is, only to v wzFor the same vertical component of wind speed, the energy consumption of the drone is the same regardless of the value of the horizontal component of wind speed. In addition, compared with a windless environment, wind disturbance does not always increase the energy consumption of the drone, which depends on the vertical wind speed angle θ. z When the vertical wind speed angle θ z When greater than 0 (θ z >0), that is, there is vertical wind disturbance from top to bottom, and the drone will be subjected to downward wind pressure. In order to resist this pressure, the drone's fuselage needs to face upward, creating an elevation angle greater than 0. At this time, the drone's engine needs to consume energy to generate forward thrust to offset the backward resistance caused by its own gravity. z When it is less than 0 (θ z <0), that is, there is vertical wind disturbance from bottom to top. In this case, the drone will be subjected to upward wind pressure, causing the fuselage to tilt downward, resulting in an elevation angle less than 0. In this case, the drone's own gravity will generate a forward force, reducing the thrust that the drone engine needs to generate, thereby reducing the engine's power consumption. In addition, Figure 2 It shows that the energy consumption of the UAV is in good agreement with the Matlab simulation results, which confirms the correctness of the proposed optimization method. Figure 3 It shows that the amount of data actually received by the ground destination node is greater than the set Q value, which confirms the correctness of the research. Figure 3 Display, headwind flight (90°<θ x <270°) will increase the amount of data received by the destination node. In fact, compared with the tailwind situation, the headwind will reduce the ground speed of the drone, and the reduction of ground speed is conducive to the forwarding of data by the drone relay.

[0179] The following table gives Figure 2 and Figure 3 The airspeed and ground speed of the drone, as well as the yaw angle and pitch angle under the four wind disturbance conditions considered in the figure. As can be seen from Table 2 below, the airspeed and yaw angle under the four conditions are the same; headwind (θ x =150°) will reduce the ground speed, which is beneficial for the UAV to forward data, that is, the amount of data received by the ground destination node will increase. Figure 3 It should be noted that: since the lower bound of the amount of data received by the destination node is used when solving the optimization problem, the flight time T of the drone (the time to complete the data forwarding task) is always equal to the amount of data Q to be forwarded divided by the lower bound.

[0180] Table 2

[0181]

[0182] Attached Figure 4 , Figure 5 , Figure 6 and Figure 7 The energy consumption of the UAV, yaw angle and pitch angle, airspeed and ground speed, the actual amount of data received by the destination node, and the vertical wind speed angle θ are given respectively. z The relationship between the vertical wind speed angle θ z The value range is [-30°, 30°], and the horizontal wind speed angle θ x =210°, the amount of data required to be forwarded is Q=100. Figure 4 It shows that when the vertical wind speed angle θ z When the value is small (θ z ≤-20°), the energy consumption of the drone is 0. This is because the vertical wind speed angle θ z When the value is small, the elevation angle of the drone is also very small and the value is less than 0, such as Figure 5 As shown in Figure 1. When the drone is subjected to upward wind pressure, the fuselage will tilt downward. For such a situation, when the vertical wind speed angle θ z When the vertical wind speed angle θ decreases, the elevation angle of the drone also decreases. At this time, the forward component of the drone's own gravity will increase. z When it decreases to the "zero power threshold", the forward component of the drone's gravity will be equal to the flight resistance. At this time, the drone's engine does not need to generate thrust, so the energy consumption is zero. z When the value of is greater than the “zero power threshold”, the energy consumption of the drone will increase with the vertical wind speed angle θ z increases monotonically. In addition, Figure 4 It shows that the two energy consumption curves under no wind and steady wind disturbance are in θ z =0, and it is consistent with the Matlab simulation result, which proves the correctness of the research.

[0183] Figure 5 Given the yaw angle, elevation angle and vertical wind speed angle θ z The relationship between. Figure 5 It shows that when the vertical wind speed angle θ z When the yaw angle φ is less than the “zero power threshold”, the vertical wind speed angle θ z The increase of the vertical wind speed angle θ z When the yaw angle φ is greater than the “zero power threshold”, the vertical wind speed angle θ z The increase of the vertical wind speed angle θ will slightly decrease. z increases monotonically.

[0184] Figure 6 It shows that when the vertical wind speed angle θ z When the airspeed and ground speed are less than the "zero power threshold", the vertical wind speed angle θ z When the vertical wind speed angle θ zWhen the wind speed is greater than the "zero power threshold", the airspeed and ground speed will also change with the vertical wind speed angle θ. z However, the decrease is very small. z When the vertical wind speed angle θ is large, the airspeed in the presence of steady wind disturbance will be slightly lower than the airspeed in the absence of wind. This is because as the vertical wind speed angle θ z As the airspeed increases, the reverse force component caused by the gravity of the drone will also increase. At this time, the drone's engine needs to generate more thrust to offset the reverse force component. In this case, reducing the airspeed can prevent the rapid increase of the drone's engine power. x =210°, the drone is flying against the wind, so the ground speed is less than the air speed. Figure 6 As shown,

[0185] Figure 7 The actual amount of data received by the ground destination node is given. In the simulation experiment here, the residual self-interference channel power is set to -60dB. Figure 7 It shows that the amount of data actually received by the ground destination node is greater than the set Q value, which proves the correctness of the research. Figure 6 ), the amount of data actually received by the ground destination node will be less than that in the case of no wind (see Figure 7 ), and vice versa, further confirming that a low ground speed is conducive to the data forwarding of the drone relay. It should be noted that the flight time of the drone here is 108.4s, which can be directly calculated using the formula T = Q / Q lb Calculated.

[0186] Attached Figure 8 , Fig. 9 , Fig.10 , Fig.11 The energy consumption of the UAV, yaw angle and elevation angle, airspeed and ground speed, the actual amount of data received by the destination node, and the horizontal wind speed angle θ are given respectively. x The relationship between x The value range of θ is [180°, 360°], z =20°, Q=100. Figure 8 It shows that the energy consumption of the drone does not change with the horizontal wind speed angle θ x This shows that the wind speed and wind volume on the horizontal plane have no effect on the energy consumption of the drone. z > 0, the drone is subject to downward wind pressure. To resist this pressure, the drone should face upward (see Fig. 9 The elevation angle α in the image is always greater than zero), which requires the engine to generate additional energy consumption. Therefore, the energy consumption of the drone at this time is greater than that in the case of no wind.

[0187] Since the vertical wind speed angle θz =20°, at this time, the component of wind speed in the vertical direction (z-axis direction) is a constant. Fig.10 It shows that the airspeed of the UAV under steady wind disturbance is at the horizontal wind speed angle θ x Therefore, according to the formula α=arcsin(v wz / ||U||), the elevation angle α is also constant, as shown in Fig. 9 In addition, Fig. 9 It shows that when the horizontal wind speed angle θ x The value range is [270°, 360°], and the yaw angle φ will change with the horizontal wind speed angle θ x increases with the increase of the horizontal wind speed angle θ x The value range is [180°, 270°], and the yaw angle φ will change with the horizontal wind speed angle θ x decreases with the increase of x When =270°, the wind speed direction will be perpendicular to the ground speed direction and the yaw angle φ will take the maximum value.

[0188] Fig.10 It shows that the airspeed of the drone is at the horizontal wind speed angle θ x This is because the vertical component of wind speed v wz The values ​​of and Q are constant. x When the value range of is [180°, 270°], the UAV will fly against the wind; when the horizontal wind speed angle θ x When the value range is [270°, 360°], the UAV will fly with the wind. x As the wind speed increases, the component of the wind speed along the ground speed direction (x-axis direction) increases. Therefore, Fig.10 It shows that when the horizontal wind speed angle θ x When the value range is [180°, 360°], the ground speed will change with the horizontal wind speed angle θ x increases monotonically. In addition, Fig.10 It shows that when the horizontal wind speed angle θ x When the value range is [270°, 285°], the ground speed is still less than the air speed. x When the value range is [270°, 285°], the drone will be in a downwind flight state. The reason for this is that the relationship between airspeed and ground speed depends not only on wind speed, but also on yaw angle.

[0189] Fig.11 The actual amount of received data at the ground destination node is given. Similarly, the residual self-interference channel power is set to -60dB. Fig.11The data actually received by the ground destination node is greater than the set Q value, which confirms the correctness of the study. Fig.10 The actual amount of data received by the ground destination node under the condition of constant wind disturbance is greater than that under the condition of no wind (see Fig.11 ), and vice versa, which further confirms that a smaller ground speed is beneficial to the data forwarding of the drone relay. It should be noted that the flight time of the drone is also equal to 108.4s, which can be directly calculated by T = Q / Q lb Calculated.

[0190] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A UAV-assisted full-duplex amplification and forwarding relay communication method under steady wind disturbance, characterized in that: The method comprises the following steps: S1, when wind speed v w The component v along the x-axis wx ≥0, when the UAV acts as a relay and flies along a horizontal straight line from the source node to the destination node with the wind, the energy minimization problem of completing the data transmission task between the ground source and the destination node is solved and the optimal solution is obtained. When v wx <0, jump to step S7; S2. When the drone acts as a relay and flies against the wind from the source node along a horizontal straight line toward the destination node, solve the energy minimization problem when completing the data transmission task between the ground source and the destination node and obtain the optimal solution. S3, if Then, when the UAV acts as a relay and flies from the source node along a horizontal straight line toward the destination node within a given time, the optimal solution to the energy minimization problem of completing the data transmission service required by the ground source and destination nodes is U * =T * =NaN, jump to step S9; S4. If The optimal solution for energy minimization in step S3 is Jump to step S9; S5. If The optimal solution for energy minimization in step S3 is Jump to step S9; S6. If The optimal solution for energy minimization in step S3 is like The optimal solution for energy minimization in step S3 is Jump to step S9; S7. When the drone acts as a relay and flies against the wind from the source node along a horizontal straight line toward the destination node, solve the energy minimization problem when completing the data transmission task between the ground source and the destination node, and obtain the optimal solution. S8, if The optimal solution for energy minimization in step S3 is U * =T * =NaN; otherwise, the optimal solution for energy minimization in step S3 is S9. End.

2. The method according to claim 1, characterized in that In step S1, the energy minimization problem when completing the data transmission task between the ground source and the destination node is expressed as: in, and They represent the optimal solution of the UAV’s airspeed U and the time T to complete the data forwarding task, En(U) represents the power consumption of the UAV when it flies at an airspeed U, and U min and U max are the minimum and maximum airspeed limits of the drone, v wx 、v wy and v wz The wind speed v w In the x, y and z axis components, Q is the amount of data that the ground source node N1 needs to send to the ground destination node N2, Q lb is the lower limit of the amount of data that the ground destination node N2 can receive per unit time, l 12 It is the distance between the ground source node N1 and the ground destination node N2.

3. The method according to claim 1, characterized in that In step S2, the energy minimization problem when completing the data transmission task between the ground source and the destination node is expressed as: s.t.U min ≤U≤U max (10b) in, and They represent the optimal solution of the UAV’s airspeed U and the time T to complete the data forwarding task, En(U) represents the power consumption of the UAV when it flies at an airspeed U, and U min and U max are the minimum and maximum airspeed limits of the drone, v w is the wind speed, v wx 、v wy and v wz The wind speed v w In the x, y and z axis components, Q is the amount of data that the ground source node N1 needs to send to the ground destination node N2, Q lb is the lower limit of the amount of data that the ground destination node N2 can receive per unit time, l 12 It is the distance between the ground source node N1 and the ground destination node N2.

4. The method according to claim 1, characterized in that In step S7, the energy minimization problem when completing the data transmission task between the ground source and the destination node is expressed as: s.t.U min ≤U≤U max (11b) U≥v w (11c) in, and They represent the optimal solution of the UAV’s airspeed U and the time T to complete the data forwarding task, En(U) represents the power consumption of the UAV when it flies at an airspeed U, and U min and U max are the minimum and maximum airspeed limits of the drone, v w is the wind speed, v wx 、v wy and v wz The wind speed v w In the x, y and z axis components, Q is the amount of data that the ground source node N1 needs to send to the ground destination node N2, Q lb is the lower limit of the amount of data that the ground destination node N2 can receive per unit time, l 12 It is the distance between the ground source node N1 and the ground destination node N2.

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