CN115942419A - Optimization method of full-duplex fixed-wing unmanned aerial vehicle relay system - Google Patents
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Abstract
The invention discloses an optimization method of a full-duplex fixed wing unmanned aerial vehicle relay system with roll angle limitation, which utilizes position information of a source node and a destination node, optimizes and adjusts the flight radius, the flight speed and the flight time of an unmanned aerial vehicle according to the size of data volume required to be sent to the destination node by the source node, the maximum minimum speed of unmanned aerial vehicle flight and the roll angle limitation, and realizes the minimization of the flight energy consumption of the unmanned aerial vehicle under the condition of meeting the flight speed and the roll angle limitation of the unmanned aerial vehicle and the requirement of system data volume sending.
Description
Technical Field
The invention belongs to the technical field of wireless communication, and particularly relates to an optimization method of a full-duplex fixed wing unmanned aerial vehicle relay system with a roll angle limit under a circular track.
Background
In recent years, the unmanned aerial vehicle cooperative communication technology becomes a hot spot of research in the field of wireless communication. Compared with the traditional ground communication, the unmanned aerial vehicle cooperative communication is easy to realize distribution as required, so that higher communication efficiency is achieved; the unmanned aerial vehicle has high mobility, so that the unmanned aerial vehicle is more flexible and rapid to deploy; the possibility that the communication link between the unmanned aerial vehicle and the ground terminal is a line-of-sight channel is higher than the ground communication condition under the same communication distance, so that better channel transmission conditions can be provided. Therefore, the unmanned aerial vehicle must play an extremely important role in the future wireless communication field, and the application thereof mainly comprises: (1) as a temporary base station; (2) as a mobile relay; and (3) the system is used for the Internet of things.
At present, a great deal of literature researches optimization problems of the capacity and the spectrum efficiency of a relay communication system when an unmanned aerial vehicle is used as a mobile relay. Indeed, drones have limited on-board energy, and energy efficiency is considered to be one of the key issues for drone communication. At present, for unmanned aerial vehicle relay communication, decoding forwarding relay communication form is mostly considered in research, and the research on the adoption of amplification forwarding relay by an unmanned aerial vehicle is less, especially amplification forwarding unmanned aerial vehicle relay communication in a full-duplex mode is not considered yet, and the research is worth. On the other hand, the problem that the flight radius and the flight speed of the fixed-wing unmanned aerial vehicle are related to the roll angle of the fixed-wing unmanned aerial vehicle under the circular track is often neglected in the past and needs to be further researched.
Disclosure of Invention
The invention aims to provide an optimization method of a full-duplex fixed wing unmanned aerial vehicle relay system with a roll angle limit under a circular track, so that the flight radius, the flight speed and the flight time of the unmanned aerial vehicle relay system are adjusted, and the flight energy consumption of the unmanned aerial vehicle is minimized under the conditions of meeting the flight speed limit and the roll angle limit of the unmanned aerial vehicle and meeting the requirement of sending data volume of the system, thereby improving the energy efficiency of the system.
The invention is realized in this way, an optimization method of a full-duplex fixed wing unmanned aerial vehicle relay system with the rolling angle limitation, utilizes the position information of a source node and a destination node, optimizes and adjusts the flight radius, the flight speed and the flight time of the unmanned aerial vehicle according to the data volume size required to be sent to the destination node by the source node, the maximum and minimum flying speeds of the unmanned aerial vehicle and the rolling angle limitation, and realizes the minimization of the flying energy consumption of the unmanned aerial vehicle under the conditions of meeting the flight speed and the rolling angle limitation of the unmanned aerial vehicle and meeting the requirement of the data volume sent by the system.
For a full-duplex fixed wing UAV relay communication system with roll angle limitation under a circular track, the system is arranged on the groundThe source node S needs to send Q data volume to a destination node D, the distance between S and D is assumed to be L, because the S and D are far away, a direct link does not exist, the data forwarding needs to be carried out by means of a fixed wing unmanned aerial vehicle relay R flying at the height of H, the unmanned aerial vehicle relay R works in a full-duplex mode (receiving and transmitting signals are carried out at the same frequency band at the same time), and an amplification-and-Forward (AF) relay protocol is adopted; the plane of the flight track of the unmanned aerial vehicle relay R is parallel to the ground plane, the projection of the flight track on the ground plane is a circle, the circle takes the midpoint of the connecting line of the source node S and the destination node D as the circle center, R as the radius and the circumferential flight speed as v; unmanned aerial vehicle flight process with roll angle limitation
(
Is less than or equal to 45 degrees), namely, the actual roll angle phi of the unmanned aerial vehicle flight needs to meet->
Assuming that wireless signal transmission channels from S to R and from R to D are mixed probability channels, that is, mixed channels in which line-of-Sight (Light of Sight, loS) and Non-line-of-Sight (Non Light of Sight, NLoS) links exist with probability conditions; thus, at time t, the S to R channel can be written as:
wherein d is SR (t) is the distance from time S to R at t, which can be specifically given by the following equation (2), θ is the wireless channel fading factor,
denotes the channel gain reference value in the case of a distance of 1m, λ is the additional fading factor in the case of an NLoS link, P r SR -LOS (t) is the probability that the LOS link between time S and R is at t, which can be given by equation (3),1-P r SR-LOS (t) is the probability of being an NLOS link between time S and R;
it should be noted that: it is assumed here that the source node S is located at (0, 0), the destination node D is located at (L, 0), and the starting point of the UAV flight is
Arcsin (-) in the formula (3) is an arcsine function, alpha and beta are mixed probability channel model parameters, and the values of the alpha and the beta depend on the specific communication geographic environment;
likewise, at time t, the R to D channel may be written as:
wherein d is RD (t) is the distance from R to D at time t, and can be specifically given by the following formula (5), P r RD-LOS (t) is the probability that there is a LOS link between R and D at time t, which can be given by equation (6) below, 1-P r RD-LOS (t) is the probability that there is an NLOS link between time t, R and D;
due to the above h SR (t) and h RD (t) mixed probability channels, both LoS and NLoS, are difficult to mathematically process, and for this purpose use is made ofH is respectively solved according to the probability of LoS and NLoS links SR (t) and h RD Average value of (t)
And &>
Specifically, the formula (7) and the formula (8) can be given respectively;
it should be noted that: in formula (7)
In formula (8)
Will be used below in conjunction with ^ 7 and ^ 8>
And &>
Respectively substitute for h SR (t) and h RD (t) performing a mathematical analysis;
because unmanned aerial vehicle relay R works in the full-duplex mode, at this moment, the wireless signal that unmanned aerial vehicle transmitting antenna launches will be received by unmanned aerial vehicle receiving antenna, for this reason unmanned aerial vehicle need adopt Loop Interference Cancellation (LIC) technique to eliminate the Loop Interference that produces under the full-duplex mode, then moment t, the signal expression that unmanned aerial vehicle relay R received:
wherein P is TX Is the transmit power of S and R; x is the number of S Is the transmit signal of S (assuming power of 1); x is the number of R A transmit signal of R (assuming power of 1); h is LI Is residual loop interference after LIC; z is a radical of R Is white Gaussian noise received by R (assuming mean 0 and variance σ 2 I.e. white Gaussian noise with an average power of σ 2 ) The unmanned plane will receive signal y R (t) multiplied by the amplification factor ρ becomes the transmitted signal, i.e., x R ＝ρy R (t) here
Suppose that the drone relays R to receive signal y R The processing of (t) is ideal enough, and without any delay, the signal received by the node D is:
wherein z is D Is D white Gaussian noise received (assuming mean 0 and variance σ) 2 )；
X is to be R ＝ρy R (t) substitution of the formula (10) and mathematical operation
The received signal-to-noise ratio of the D node can be obtained from equation (11), which can be specifically written as:
wherein
Thus, the amount of data that can be received by the destination node at time t is:
according to the above analysis, the problem of minimum optimization of energy consumption of the unmanned aerial vehicle can be written as
s.t.Q-Q D (T)≤0 (14b)
V min ≤v≤V max (14c)
φ≤ω (14d)
Here, T is the time to complete the Q data volume forwarding,
the power consumption of the fixed-wing unmanned aerial vehicle flying in a circular track with constant speed v and radius r, wherein g represents the gravity acceleration, and c represents the power consumption 1 ＝ηC D0 B/2、c 2 ＝2W 2 /[(πe 0 A R )ηB]Eta represents air density, C D0 Denotes the zero lift drag coefficient, B denotes the wing area, e 0 Is the span efficiency, W represents the overall weight of the drone, A R Aspect ratio, V, of the unmanned wing max And V min The maximum flight speed and the minimum flight speed of the unmanned aerial vehicle are respectively, the constraint condition formula (14 d) shows that the actual roll angle phi of the unmanned aerial vehicle needs to meet the roll angle limit of the unmanned aerial vehicle, namely, the actual roll angle phi is less than or equal to the maximum roll angle ^ supported by the unmanned aerial vehicle>
(
The value of (1) is less than or equal to 45 degrees);
it should be noted that: the flying speed v and the flying radius r of the fixed-wing unmanned aerial vehicle meet the requirements of the fixed-wing unmanned aerial vehicle on a circular track
Where φ is the actual roll angle of the drone, and->
The need always holds;
to understand the optimization problem (14), i.e., the optimization problem composed of the formula (14 a), the formula (14 b), the formula (14 c), and the formula (14 d), the constraint formula (14 b) is simplified; for this purpose, log is first given 2 [1+γ D (t)]The lower bound of (c) can be specifically written as:
then according to the inequality
And formula (15), log can be found further 2 [1+γ D (t)]The lower bound of (1) can be specifically written as:
when in use
When, is greater or less>
P r SR-LOS (t)＝P r RD-LOS (t)，
Has a maximum value, and therefore can obtain log 2 [1+γ D (t)]The lower bound of (1) can be specifically written as:
it should be noted that: in formula (17)
And &>
Is a function of r only, and is independent of v;
from equations (13) and (17), the lower bound of the amount of data that can be received by the destination node D at time t is given by:
wherein,
q obtained by the following formula (19) D Lower boundary of (t)
To replace Q D (t) and converting phi ≦ ω
The problem of energy consumption minimization optimization of the drone, i.e. the problem (14) can be transformed into
V min ≤v≤V max (20c)
It should be noted that: when the lower bound of the data which can be received by the destination node D is greater than or equal to Q, the data which can be actually received by the destination node D is definitely greater than or equal to Q;
to understand the problem (20), i.e., the optimization problem composed of the formula (20 a), the formula (20 b), the formula (20 c), and the formula (20 d), first, constraint conditions are simplified;
the observation of formula (19) can find
Is an increasing function of t, so when the objective function (20 a) of the problem (20) takes the minimum value, the equation (20 b) will take the equal sign, otherwise the value of equation (20 a) will be further reduced by shortening the time and the constraint condition is satisfied; when the formula (20 b) takes an equal sign, there are
It should be noted that: t in the formula (21) is independent of v and is only an increasing function of r;
the relational expression among the flight speed, the flight radius and the actual roll angle of the unmanned aerial vehicle can be obtained
Will then->
Substitution into P W (r, v), obtaining:
the partial derivative of tan. Phi. Is obtained for equation (22) and made 0
That is, when equation (22) takes a minimum value, equation (23) holds;
from the formulae (20 c) and (20 d)
Always true; t given in equation (21) is an increasing function of r; let the corresponding flying radius of the unmanned aerial vehicle be r when the formula (22) takes the minimum value 1 If the target function expression (20 a) of the problem (20) is the minimum value, the flight radius r of the unmanned aerial vehicle * Must satisfy->
To do this, first a one-dimensional search algorithm is used (reference: solution of novelty, hanlixing, forest friend connection. Optimization method [ M)]Tianjin-Tianjin university Press 1997.13-26.) solution problem (24), i.e. the optimization problem composed of equation (24 a) and equation (24 b), where the one-dimensional search is to find the flight radius r of the drone when equation (24 a) takes the minimum value within the range of flight radii given by equation (24 b) 2 ；
Wherein Q is the data quantity sent by the source node S to the destination node D, r is the radius of the unmanned aerial vehicle performing circular flight motion at a constant speed v,
is the roll angle limit and the judgment of the unmanned plane in the flying process>
Less than or equal to 45 degrees and V min For the minimum flying speed of the unmanned plane, e represents the natural constant, σ 2 Represents the variance of Gaussian white noise, and->
The power consumption of the fixed-wing unmanned aerial vehicle flying in a circular track with constant speed v and radius r, wherein g represents the gravity acceleration, and c represents the power consumption 1 ＝ηC D0 B/2，c 2 ＝2W 2 /[(πe 0 A R )ηB]Wherein eta represents air density, C D0 Denotes the zero lift drag coefficient, B denotes the wing area, e 0 Is the wingspan efficiency, W represents the overall weight of the drone, A R Represents the aspect ratio of the unmanned wing, </or > is >>
Wherein P is TX Is the emission power of S and R>
And &>
The average channel gains at time t for S to R and R to D, respectively.
Then, r is 2 Substituting r into the formula (23), calculating the tangent value tan phi of the actual rolling angle phi of the unmanned aerial vehicle at the moment, and if the tangent value tan phi is not equal to the actual rolling angle phi of the unmanned aerial vehicle at the moment
If this is true, the corresponding flight speed is calculated at this time>
If it is
Is established, then r 2 Is the optimum flying speed r of the problem (20) * The corresponding optimal flight speed is:
if it is
Optimum flying speed v of problem (20) * ＝V min Corresponding optimum flight radius r * Can be calculated from equation (26):
if it is
Optimum flying speed v of problem (20) * ＝V max Corresponding optimum flight radius r * Can be calculated from equation (27):
if r is to 2 Substituting r into the formula (23), and calculating that the tangent value tan phi of the actual rolling angle phi of the unmanned aerial vehicle does not meet the requirement
The actual roll angle phi of the unmanned plane is made to be the maximum roll angle->
Then, solving the problem (28) by using a one-dimensional search algorithm, namely, solving an optimization problem formed by a formula (28 a) and a formula (28 b), wherein the one-dimensional search is to perform one-dimensional search on the formula (28 a) within the range of the flight radius given by the formula (28 b) to obtain the corresponding flight radius r of the unmanned aerial vehicle 3 ；
At this time, the flight radius r 3 Corresponding to a flight speed of
Due to r 3 Is searched for in the range given by equation (28 b) and, therefore, is based on>
Establishing;
if it is
Is established, then r 3 Is the optimum flight radius r of the problem (20) * The optimal flight speed at this time is:
if it is
The optimal flight speed of the problem (20) is then v * ＝V max The optimal flight radius at this time can be calculated by equation (30);
finally, the optimal flight radius r to be obtained * The optimum flight time T can be calculated by substituting r into equation (21) * 。
The method for solving the problem of minimum optimization of energy consumption of the unmanned aerial vehicle is given as follows:
step 1: solving the problem (24) by using a one-dimensional search algorithm to obtain the flight radius r of the unmanned aerial vehicle 2 ；
Step 2: will r is 2 Substituting r into formula (23) to obtain tan phi;
and step 3: if it is
If true, the corresponding flight speed at that time is calculated>
Otherwise, jumping to step 6;
and 4, step 4: if it is
If it is true, the optimum flight radius r * ＝r 2 Optimum flying speed v * Can be calculated by the formula (25), and then the step 9 is skipped;
and 5: if it is
The optimum flying speed v * ＝V min Optimum flight radius r * Can be calculated by the formula (26), and then the step 9 is skipped;
and 5: if it is
If so, the optimum flying speed v * ＝V max Optimum flight radius r * Can be calculated by the formula (27), and then the step 9 is skipped;
step 6: if it is
Solving the problem (28) by using a one-dimensional search algorithm to obtain the flight radius r of the unmanned aerial vehicle 3 ；
And 7: if it is
If it is true, the optimum flight radius r * ＝r 3 Optimum flying speed v * Can be calculated by equation (29), and then jump to step 9;
and 8: if it is
If it is true, the optimal flying speed is v * ＝V max Optimum flight radius r * Can be calculated from equation (30);
and step 9: will optimize the flight radius r * The optimum flight time T is calculated as r by substituting equation (21) * ；
Step 10: the algorithm ends.
Compared with the defects and shortcomings of the prior art, the invention has the following beneficial effects: according to the method, the flight speed, the flight radius and the flight time of the unmanned aerial vehicle are optimally adjusted by utilizing the position information of the source node and the destination node according to the maximum and minimum flight speed limit of the unmanned aerial vehicle, the maximum roll angle limit of the unmanned aerial vehicle and the data volume which needs to be sent to the destination node by the source node. The method can achieve minimization of flight energy consumption of the unmanned aerial vehicle under the condition that the requirement of system data volume sending and the limitation condition of the maximum roll angle are met, and simulation experiments also show that the optimization method has advantages in energy consumption.
Drawings
FIG. 1 is a schematic view of the process of the present invention;
FIG. 2 is a comparison of energy consumption at minimum and maximum flight speeds of the UAV using the proposed optimization method at different values of L;
fig. 3 shows the actual data volume received by the destination node at the minimum and maximum flight speeds of the unmanned aerial vehicle and the proposed optimization method under different L values;
FIG. 4 shows the flight speed of the UAV using the proposed optimization method at different values of L;
FIG. 5 shows the actual roll angle of the UAV under the minimum and maximum flight speeds of the UAV using the proposed optimization method under different values of L;
FIG. 6 is a comparison of energy consumption at minimum and maximum flight speeds of the UAV using the proposed optimization method at different Q values;
FIG. 7 shows the actual data volume received by the destination node at the minimum and maximum flight speeds of the unmanned aerial vehicle using the proposed optimization method under different Q values;
FIG. 8 shows the flight speed of the UAV using the proposed optimization method at different Q values;
FIG. 9 shows the actual roll angles of the UAV at minimum and maximum flight speeds of the UAV using the proposed optimization method at different Q values;
FIG. 10 shows a variation
Comparing the energy consumption under the minimum and maximum flight speeds of the unmanned aerial vehicle by adopting the provided optimization method under the value;
FIG. 11 is a schematic view of the difference
The data volume actually received by the target node under the minimum and maximum flight speeds of the unmanned aerial vehicle is obtained by adopting the optimization method under the value;
FIG. 12 shows a variation
Adopting the provided optimization method to obtain the flight speed of the unmanned aerial vehicle under the value;
FIG. 13 is a schematic view showing the difference
And the actual roll angle of the unmanned aerial vehicle under the minimum and maximum flight speeds of the unmanned aerial vehicle is obtained by adopting the provided optimization method under the value.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
As shown in fig. 1, the unmanned aerial vehicle relay R always flies at a height H, the projection of the flight trajectory on the ground plane is circular, the circle uses the midpoint of the connecting line between the source node S and the destination node as the center of circle, R is the radius, the projection of the starting point of the unmanned aerial vehicle on the ground plane is that the midpoint of the connecting line between the source node S and the destination node deviates from the direction of the node S, and the linear velocity of the flight of the unmanned aerial vehicle relay R is v. Unmanned aerial vehicle R sends signal to the destination program while receiving SThe point forwards the message. The unmanned aerial vehicle receives signals and forwards messages at the same time on the same frequency band, namely, the unmanned aerial vehicle works in a full duplex mode, and an AF protocol is adopted for relay forwarding. Before the unmanned aerial vehicle flies formally, aiming at an optimization problem (24), r is obtained through one-dimensional search 2 (ii) a It should be noted that: when performing one-dimensional search, the upper limit of r is originally infinite, and a large number, for example, lx10, can be set in practical operation 9 (ii) a Then, r is 2 Calculating to obtain tan phi by substituting formula (23); next, it is examined whether or not tan. Phi. Is equal to or less
If tan phi is less than or equal to +>
Then calculate r 2 Corresponding flight speed>
If>
Then r is 2 Is the optimum flight radius r * Optimum flying speed v * Can be calculated from formula (25); if/or>
The optimum flying speed v * ＝V min Optimum flight radius r * Can be calculated from formula (26); if>
The optimum flying speed v * ＝V max Optimum flight radius r * Can be calculated from formula (27); if the above-calculated tan φ is greater than->
Then the unmanned plane is enabled to be based on the maximum roll angle>
Flying, solving the problem (28) by using a one-dimensional search algorithm to obtain the flying radius r of the unmanned aerial vehicle 3 (ii) a Then, r is calculated 3 Corresponding flight speed>
Checking below>
Whether the flight speed limit is met; if/or>
Then the optimum flight radius r * ＝r 3 Optimum flying speed v * Can be calculated by equation (29); if it is
The optimum flying speed is v * ＝V max Optimum flight radius r * Can be calculated from equation (30); finally, according to the obtained optimal flight radius r * The optimum flight time T is calculated as r by substituting the equation (21) * 。
Aiming at the optimization method provided by the invention, the method carries out simulation experiments and compares the system power consumption with the system power consumption of the unmanned aerial vehicle flying at the minimum speed and the maximum speed, and the experimental environment is the Matlab environment. Suppose that the minimum and maximum speeds of the unmanned plane flight are v respectively min ＝5m/s、v max =50m/s, the signal transmission power of the unmanned aerial vehicle flying at a fixed height H =100m, and the S and R nodes is P TX = -20dBm, variance σ of white Gaussian noise in the environment 2 = 170dBm, unit distance channel gain
Channel fading factor θ =3, mixed probability channel model parameters α =4.88, β =0.43 (corresponding to rural geographical environment), additional fading factor λ = -10db in case of NLoS link, c 1 ＝9.26×10 -4 ，c 2 ＝2250，|h LI | 2 ＝10 -6 。
Fig. 2, fig. 3, fig. 4, and fig. 5 show energy consumption comparison, actual data volume received by the destination node, flight speed of the unmanned aerial vehicle, and actual roll angle of the unmanned aerial vehicle, respectively, using the optimization method under different L values, and using the method at minimum and maximum flight speeds of the unmanned aerial vehicle. Here, it is assumed that Q =100,
"V" in the figure min "and" V max "means that the drone flies at minimum and maximum flight speeds, respectively, but the flight radius and flight time are both optimized," the proposed optimization algorithm "is the result obtained by using the proposed optimization method, i.e. the result obtained by using the joint adjustment algorithm of the flight speed, flight radius and flight time of the drone," simulation "means that the given value is the result obtained by the interior point method in the Matlab optimization toolkit.
Fig. 2 shows that the proposed optimization algorithm has performance advantages in power consumption; fig. 3 shows that the data amount actually received by the destination node is greater than the set Q value, which illustrates the correctness of the proposed algorithm; fig. 4 shows that the actual flight speed of the drone meets given constraints, illustrating the correctness of the proposed algorithm; FIG. 5 shows that the actual roll angles of the drones are all less than or equal to a given limit
Illustrating the correctness of the proposed algorithm. In addition, the result obtained by the interior point method in the Matlab optimization tool box is consistent with the result given by the optimization algorithm, and the correctness of the algorithm is proved.
Fig. 6, 7, 8, and 9 show energy consumption comparison, actual data volume received by the destination node, actual flight speed of the drone, and actual roll angle of the drone, using the optimization method under different Q values, respectively, and using the minimum and maximum flight speeds of the drone. Here, it is assumed that L =2000,
FIG. 6 shows the proposed optimization algorithmHave performance advantages in power consumption; fig. 7 shows that the data amount actually received by the destination node is greater than the set Q value, which illustrates the correctness of the proposed algorithm; fig. 8 shows that the actual flight speed of the drone meets given constraints, illustrating the correctness of the proposed algorithm; fig. 9 shows that the actual roll angles of the drones are all less than or equal to the given limit
Illustrating the correctness of the proposed algorithm. In addition, the result obtained by the interior point method in the Matlab optimization tool box is consistent with the result given by the optimization algorithm, and the correctness of the algorithm is proved.
Fig. 10, 11, 12 and 13 show the differences, respectively
And under the condition of the value, an optimization method is adopted to compare the energy consumption with the energy consumption of the unmanned aerial vehicle at the minimum and maximum flight speeds, the actual data receiving quantity of the target node, the flight speed of the unmanned aerial vehicle and the actual roll angle of the unmanned aerial vehicle. Here, L =2000 and Q =100 are assumed.
Fig. 10 shows that the proposed optimization algorithm has performance advantages in power consumption; fig. 11 shows that the data amount actually received by the destination node is greater than the set Q value, which illustrates the correctness of the proposed algorithm; fig. 12 shows that the actual flight speed of the drone meets given constraints, illustrating the correctness of the proposed algorithm; FIG. 13 shows that the actual roll angles of the drones are all less than or equal to a given limit
Illustrating the correctness of the proposed algorithm. In addition, the result obtained by the interior point method in the Matlab optimization tool box is consistent with the result given by the optimization algorithm, and the correctness of the algorithm is further proved.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents and improvements made within the spirit and principle of the present invention are intended to be included within the scope of the present invention.
Claims (1)
1. A method of optimizing a full-duplex fixed wing drone relay system with roll angle limitation, the method comprising the steps of:
step 1: in the flight radius range given by the formula (24 b), solving a problem (24 a) by using a one-dimensional search algorithm to obtain the flight radius r of the unmanned aerial vehicle 2 ；
Wherein Q is the data quantity sent by the source node S to the destination node D, r is the radius of the unmanned aerial vehicle performing circular flight motion at a constant speed v,
is the roll angle limit and the judgment of the unmanned plane in the flying process>
Less than or equal to 45 degrees and V min For the minimum flight speed of the unmanned plane, e represents a natural constant, σ 2 Variance representing Gaussian white noise>
The power consumption of the fixed-wing unmanned aerial vehicle flying in a circular track at constant speed v and radius r, wherein g represents the gravity acceleration, c 1 ＝ηC D0 B/2，c 2 ＝2W 2 /[(πe 0 A R )ηB]Wherein eta represents air density, C D0 Denotes the zero lift drag coefficient, B denotes the wing area, e 0 Is the span efficiency, W represents the overall weight of the drone, A R Represents the aspect ratio of the unmanned wing, </or > is >>
Wherein P is TX Is the emission power of S and R>
And &>
Average channel gains at time t for S to R and R to D, respectively;
step 2: will r is 2 Substituting r into formula (23) to obtain tan phi;
wherein phi is the actual roll angle of the unmanned aerial vehicle flight and is required
If true;
and step 3: if it is
If this is true, the corresponding flight speed is calculated at this time>
Otherwise, jumping to step 6;
and 4, step 4: if it is
If it is true, the optimum flight radius r * ＝r 2 Optimum flying speed v * Can be calculated by the formula (25), and then the step 9 is skipped;
wherein, V max The maximum flight speed of the unmanned aerial vehicle;
and 5: if it is
The optimum flying speed v * ＝V min Optimum flight radius r * Can be calculated by the formula (26), and then the step 9 is skipped;
and 5: if it is
If so, the optimum flying speed v * ＝V max Optimum flight radius r * Can be calculated by the formula (27), and then the step 9 is skipped;
step 6: if it is
Solving the problem (28 a) by using a one-dimensional search algorithm within the flight radius range given by the formula (28 b) to obtain the flight radius r of the unmanned aerial vehicle 3 ；
And 7: if it is
If it is true, the optimum flight radius r * ＝r 3 Optimum flying speed v * Can be calculated by equation (29), and then go to step 9;
and 8: if it is
If it is true, the optimum flight speed is v * ＝V max Optimum flight radius r * Can be calculated from equation (30);
and step 9: will optimize the flight radius r * The optimum flight time T is calculated as r by substituting the equation (21) * ；
Wherein T is the time for the unmanned aerial vehicle to finish Q data forwarding.
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