A method and system for trajectory and resource optimization of a uav secure communication system

Abstract

This invention discloses a method and system for optimizing the trajectory and resources of a UAV secure communication system. The method initializes a downlink relay network system model for the UAV and sets the parameters of the communication link channel model. It initializes the UAV flight trajectory and transmission power, sets the error radii for the UAV's flight altitude, ground user location, and eavesdropper location, and performs D2D pairing based on the user-selected pairing method. The method initializes the iteration count to 0 and sets a threshold as the termination condition for the iteration of the UAV trajectory and resource optimization method based on continuous convex approximation. After each iteration, the rate of change of the security rate is calculated. If the rate of change of the security rate is greater than the set threshold, the iteration continues; otherwise, the iteration terminates. After the iteration is complete, a UAV flight trajectory and resource allocation scheme that improves the system's security performance is obtained, achieving trajectory and resource optimization. This invention provides high security performance for the communication system even when the eavesdropper's location is uncertain.

Description

Technical Field

[0001] This invention belongs to the field of information technology, specifically relating to a method and system for optimizing the trajectory and resources of a drone safety communication system. Background Technology

[0002] In certain special circumstances, such as short-term gatherings of people or natural disasters, ground base stations may be unable to meet the communication needs of all users in the area due to performance limitations or damage. Introducing drones as auxiliary communication base stations can effectively solve these problems.

[0003] D2D technology, or direct-to-device communication, is a popular technology in the field of communications today. D2D communication technology features low cost, low latency, and low power consumption. Air-to-ground communication networks supporting D2D technology have higher spectrum utilization and network coverage, while reducing the load on drone base stations. Compared to traditional cellular mobile networks, it provides higher communication network performance and improves the flexibility of air-to-ground communication networks.

[0004] However, due to the inherent openness of wireless communication, both the air-to-ground communication links and the D2D communication links in D2D-assisted UAV air-to-ground communication networks are vulnerable to eavesdropping, leading to unauthorized information interception and posing a serious security threat. Traditional methods for ensuring data confidentiality involve encrypting data transmission using encryption algorithms. Even if illegally intercepted by a third party, the encrypted data is difficult to extract useful information from. However, existing encryption algorithms are generally highly complex and difficult to apply in UAV communication systems where computing and energy resources are limited. This has become a serious obstacle to the widespread development of UAV communication services.

[0005] Physical layer security technology can leverage the inherent characteristics of the channel to achieve secure communication without increasing the computational and energy burden on the UAV. However, existing research rarely focuses on designing secure communication schemes for UAV-assisted communication networks using physical layer security technology, taking into account the uncertainty of the eavesdropper's location, for D2D-based multi-hop communication networks. Summary of the Invention

[0006] The technical problem to be solved by the present invention is to provide a method and system for optimizing the trajectory and resources of a UAV secure communication system, which addresses the shortcomings of the prior art and solves the technical problem that information is easily stolen by illegal eavesdroppers.

[0007] The present invention adopts the following technical solution:

[0008] A method for trajectory and resource optimization in a UAV secure communication system includes the following steps:

[0009] S1. Initialize the UAV downlink relay network system and set the parameters of the communication link channel model;

[0010] S2. In the UAV downlink relay network system established in step S1, the error radius of the UAV's flight altitude, ground user location, and eavesdropper location is set, and D2D pairing is performed using a random pairing method to obtain the communication method for ground users to access the network.

[0011] S3. Initialize user scheduling, UAV transmission power and UAV flight trajectory, and initialize the iteration number of the UAV trajectory and resource optimization algorithm based on continuous convex approximation to 0. Set a threshold as the iteration termination condition of the optimization algorithm, and then perform optimization algorithm iteration. Record the change rate of the confidentiality rate of the ground user access network communication method obtained in step S2 after each iteration. Continue iteration when the change rate of the confidentiality rate is greater than or equal to the set threshold; otherwise, exit the iteration.

[0012] After the optimization algorithm iterations in steps S4 and S3 are completed, the UAV flight trajectory and resource allocation scheme are obtained, thus achieving trajectory and resource optimization.

[0013] Specifically, in step S1, the parameters of the communication link channel model include:

[0014] The bandwidth W1 of the air-to-ground link, the bandwidth W2 of the ground link, the reference power gain ρ0 of the air-to-ground A2G channel at a distance of 1 meter, and the reference power gain ρ of the ground channel at a distance of 1 meter. d The transmit power P[n] of the UAV within any time slot n, and the maximum transmit power P of the UAV. max The average transmit power of the UAV, P avg Transmit power P of hybrid relay users d Gaussian white noise power σ 2 The fading coefficient k follows an exponential distribution. ij [n], the drone's flight altitude H, and the drone's maximum flight speed V. max Total number of users M, total number of time slots N, time slot length δ, and the projected coordinates w of the UAV's position on the ground. u The location coordinates w of ground user i i The location coordinates w of ground user j j The location coordinates of the eavesdropper w e The location coordinates w of the hybrid relay user r In any time slot n, the channel gain g between the drone and the eavesdropper. ue [n], the channel gain g between the hybrid relay user and the eavesdropper in any time slot n. re [n] represents the reachable rate R between the UAV and the authorized ground user within any time slot n. ui[n] represents the achievable rate R between the drone and the eavesdropper within any time slot n. ue [n], the achievable rate R between ground user i and ground user j within any time slot n. ij [n], the connection status x between the drone and ground user i during time interval n. i [n], the flag y indicating whether a D2D communication link can be established between ground user i and ground user j within any time slot n. ij [n] is a flag indicating whether ground user i is a hybrid relay user and whether it has successfully established a D2D communication link with D2D user j within any time slot n. ij [n] represents the communication security rate between the UAV and ground user i in any time slot n when the UAV communicates directly with ground user i. When a drone first communicates with a hybrid relay user, transmitting confidential information to the hybrid relay user, and then the hybrid relay user transmits the confidential information to a D2D user via the established D2D communication link, what is the confidentiality rate of this communication process within any time slot n? The overall security rate R of the UAV downlink relay network system s .

[0015] Specifically, in step S3, the optimization algorithm iteration is performed as follows:

[0016] S301, Initialize User Scheduling S k UAV transmission power P k and drone flight trajectory O k The algorithm iteration count k is initialized to 0, and a confidentiality rate change threshold ε is set as the iteration termination condition for the optimization algorithm.

[0017] S302, at a given UAV transmit power P k and drone flight trajectory O k Below, let the flag bit x indicate whether the UAV serves ground user i at any given time n. i [n] takes values ​​between 0 and 1, and the drone serves at most one ground user in the same time slot, i.e., for x i The constraint that the summation from i=1 to M is less than or equal to 1 is used to optimize the user schedule, resulting in the optimized user schedule S. k+1 ;

[0018] S303, on the given drone flight trajectory O k The user schedule S obtained after optimization in step S302 k+1 Under the condition that the UAV's transmit power P[n] is less than or equal to the maximum transmit power P at any time n. maxFurthermore, the value must be greater than or equal to 0, and the sum of the UAV's transmit power at all times divided by the total number of times N must be less than or equal to the average transmit power P. avg As a constraint, the UAV's transmit power is optimized to obtain the optimized UAV transmit power P. k+1 ;

[0019] S304. Utilize the user scheduling S obtained after optimization in step S302. k+1 The UAV transmit power P obtained after optimization in step S303 k+1 The drone flight trajectory is optimized using the following constraints: the start and end points of the drone's flight trajectory are the same within a service cycle; the square of the drone's flight distance at any given time is less than or equal to the square of the product of the drone's maximum flight speed and the time slot length; and two constraints on slack variables. The optimized drone flight trajectory O is obtained. k+1 ;

[0020] S305. Increment the iteration count k by 1, and optimize the user schedule S based on the result obtained in step S302. k+1 The UAV transmit power P obtained after S303 optimization k+1 The UAV flight trajectory O obtained after optimization with S304 k+1 Overall security rate R of the computing system s And calculate the rate of change of the confidentiality rate ΔR. s When the rate of change in confidentiality ΔR s When the value is greater than or equal to a pre-set threshold ε, the S obtained in this iteration of optimization is... k+1 P k+1 and O k+1 S is given in the next iteration. k P k and O k Continue executing step S302 to perform the iterative optimization process; otherwise, terminate the iterative optimization process.

[0021] Furthermore, step S302 specifically includes:

[0022] Calculate the reachability R from the UAV to the legitimate ground user in any time slot n. ui [n], the achievable speed R from the drone to the eavesdropper ue [n] and the reachable rate R between ground user i and ground user j ij [n], a flag indicating whether the UAV is serving ground user i at any time n. i [n] takes a value between 0 and 1, and in the same time slot, the drone serves at most one ground user, i.e., for x i[n] The sum of [n] from i=1 to M is less than or equal to 1 as a constraint. The optimization objective is to maximize the overall security rate of the system, given the UAV's transmit power P. k and drone flight trajectory O k Based on this, an optimization process is performed to obtain the optimized user schedule S. k+1 And calculate the optimized overall system security rate R. s Finally, the security rate is processed. If the total security rate of the eavesdropping channel is greater than that of the legitimate channel, communication between the UAV and the ground user is suspended at the corresponding time. The security rates at these times are removed from the calculation of the overall system security rate, and the optimized user scheduling S is recorded. k+1 And the overall system security rate R s .

[0023] Furthermore, within any time slot n, the achievable rate R between the drone and the legitimate ground user... ui [n] is calculated as follows:

[0024]

[0025] The achievable rate R between drones and eavesdroppers ue [n] is calculated as follows:

[0026]

[0027] The reachable rate R between ground user i and ground user j ij [n] is calculated as follows:

[0028]

[0029] Where W1 represents the bandwidth of the air-to-ground link, W2 represents the bandwidth of the ground link, ρ0 represents the A2G (air-to-ground) channel reference power gain at a distance of 1 meter, and ρ d Let P[n] represent the ground channel reference power gain at a distance of 1 meter, and P[n] represent the UAV transmit power within any time slot n. d For the transmit power of hybrid relay users, σ 2 This represents the Gaussian white noise power, where H is the drone's flight altitude, and k is the power. ij [n] represents the fading coefficient, which follows an exponential distribution. u w represents the projected coordinates of the drone's position on the ground. i and w j Let w represent the location coordinates of ground user i and ground user j respectively. e Then, ||·|| represents the location coordinates of the eavesdropper, ||·|| represents the Euclidean norm, and ||w u -w i|| represents the Euclidean distance between the drone's position projected onto the ground and the ground user's position, ||w e -w i ||and||w i -w j || represent the Euclidean distance between the drone's position projected onto the ground and the eavesdropper's position, as well as the Euclidean distance between ground user i and ground user j, respectively;

[0030] In a UAV downlink relay network, the system's security level R s Represented as:

[0031]

[0032] x ij [n] = x i [n]y ij [n]

[0033] Among them, y ij [n] is a flag indicating whether a D2D communication link can be established between ground user i and ground user j, x i [n] represents the connection status between the drone and ground user i within time interval n, x ij [n] = 1 indicates that the ground user i being served by the UAV is a hybrid relay user, and that user has successfully established a D2D communication link with D2D user j. In the case where the UAV communicates directly with ground user i, the communication security rate between the UAV and ground user i is... The confidentiality rate of the communication process within any time slot n is calculated when the UAV first communicates with the hybrid relay user, transmitting confidential information to the hybrid relay user, and then the hybrid relay user transmits the confidential information to the D2D user through the established D2D communication link.

[0034] Furthermore, step S303 specifically includes:

[0035] The UAV's transmit power P[n] at any given time n is less than or equal to the maximum transmit power P. max Furthermore, the result of summing the UAV transmit power at all times and dividing by the total number of times N is less than or equal to the average transmit power P. avg As a constraint, with the optimization objective of maximizing the overall security rate of the system, given the UAV flight trajectory O k And the user schedule S obtained after optimization using step S302 k+1 Based on this, an optimization process is performed on the UAV's transmission power to obtain the optimized UAV transmission power P. k+1 Then, the achievable rate R was calculated. ui [n]、Rue [n] and R ij [n], and calculate the overall security rate of the system; finally, process the security rate by removing the security rates at times when the total security rate of the eavesdropping channel is greater than the total security rate of the legitimate channel from the calculation of the overall system security rate, and record the optimized UAV transmit power P. k+1 And the overall system security rate R s .

[0036] Furthermore, step S304 specifically involves:

[0037] Using constraints such as the same start and end point of the UAV flight trajectory within a service cycle, the square of the UAV flight distance at any time being less than or equal to the square of the product of the UAV's maximum flight speed and the time slot length, and two constraints on slack variables, the optimization objective is to maximize the overall security rate of the system. The user scheduling S obtained after optimization using step S302 is then optimized. k+1 The UAV transmit power P obtained after optimization using step S303 is... k+1 Based on this, an optimization process is performed on the drone's flight trajectory to obtain the optimized drone flight trajectory O. k+1 Then, the achievable rate R was calculated. ui [n]、R ue [n] and R ij [n], and calculate the overall security rate of the system; finally, process the security rate by removing the security rates at times when the total security rate of the eavesdropping channel is greater than the total security rate of the legitimate channel from the calculation of the overall system security rate, and record the optimized UAV flight trajectory O. k+1 And the overall system security rate R s .

[0038] Secondly, embodiments of the present invention provide a trajectory and resource optimization system for a UAV safe communication system, comprising:

[0039] The initial module initializes the UAV downlink relay network system and sets the parameters of the communication link channel model.

[0040] The pairing module sets the error radius of the UAV's flight altitude, ground user location, and eavesdropper location in the UAV downlink relay network system established by the initial module, and performs D2D pairing in a random pairing manner to obtain the communication method for ground users to access the network.

[0041] The iteration module initializes user scheduling, UAV transmission power, and UAV flight trajectory, and initializes the iteration count of the UAV trajectory and resource optimization algorithm based on continuous convex approximation to 0. A threshold is set as the iteration termination condition for the optimization algorithm. The optimization algorithm is then iterated, and the change rate of the confidentiality rate of the ground user access network communication method obtained by the pairing module after each iteration is recorded. If the change rate of the confidentiality rate is greater than or equal to the set threshold, the iteration continues; otherwise, the iteration exits.

[0042] The optimization module and the iteration module optimize the algorithm. After the algorithm completes the iteration, the UAV flight trajectory and resource allocation scheme are obtained, thus realizing trajectory and resource optimization.

[0043] Thirdly, a computer device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the above-described UAV safe communication system trajectory and resource optimization method.

[0044] Fourthly, embodiments of the present invention provide a computer-readable storage medium including a computer program, which, when executed by a processor, implements the steps of the above-described UAV safe communication system trajectory and resource optimization method.

[0045] Compared with the prior art, the present invention has at least the following beneficial effects:

[0046] This invention discloses a trajectory and resource optimization method for a drone secure communication system, considering a drone air-to-ground network based on D2D-assisted communication. D2D technology allows direct communication between physically adjacent devices. Communication networks supporting D2D technology not only provide lower communication latency and power consumption, reducing the burden on drone base stations, but also improve network coverage and spectrum efficiency. Furthermore, it incorporates consideration of the uncertainty of eavesdropper locations, making the network model more realistic and universally applicable. After optimization using the algorithm employed in this invention, the overall system security rate in scenarios with uncertain eavesdropper locations is very close to that in scenarios with determined eavesdropper locations. This demonstrates the effectiveness and robustness of the algorithm used in this invention, proving that it can provide high security performance for the communication system even when the eavesdropper's location is uncertain.

[0047] Furthermore, the parameters in the communication link channel model are described in detail. These parameters can be used to accurately characterize the channel state and the communication state in the network, and facilitate the calculation of the overall security rate of the system.

[0048] Furthermore, the alternating iterative optimization method used in this invention can fully tap the potential of user scheduling, UAV transmission power, and UAV flight trajectory to improve the overall security of the system, and facilitates the setting of iteration termination conditions for the optimization algorithm.

[0049] Furthermore, the method in step S302 can further adjust the user scheduling to improve the system's security by combining the given or previously obtained UAV flight trajectory and transmission power.

[0050] Furthermore, the achievable rate R for introducing drones to legitimate ground users ui [n], the achievable speed R from the drone to the eavesdropper ue [n] and the reachable rate R between ground user i and ground user j ij [n] is used to accurately assess the system's security level.

[0051] Furthermore, the method in step S303 can further adjust the UAV transmission power to improve the system's security by combining the given user schedule and UAV flight trajectory obtained after the previous optimization algorithm iteration.

[0052] Furthermore, the method in step S304 can further adjust the UAV flight trajectory to improve the system's security by combining the given user schedule and UAV transmission power obtained after the previous optimization algorithm iteration.

[0053] It is understood that the beneficial effects of the second to fourth aspects mentioned above can be found in the relevant descriptions in the first aspect mentioned above, and will not be repeated here.

[0054] In summary, this invention designs a secure communication scheme for UAV-assisted communication networks based on D2D multi-hop communication networks. It incorporates consideration of the uncertainty of the eavesdropper's location. After optimization using the algorithm employed in this invention, the overall system security rate in scenarios with uncertain eavesdropper locations is very close to that in scenarios with determined eavesdropper locations. This demonstrates the effectiveness and robustness of this method, proving that it can provide high security performance for the communication system even when the eavesdropper's location is uncertain.

[0055] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0056] Figure 1 A diagram of a UAV downlink relay network system;

[0057] Figure 2A schematic diagram illustrating the drone trajectory before and after optimization under different drone flight altitudes and uncertainties in the location of the eavesdropper;

[0058] Figure 3 The graph shows the change in confidentiality rate as a function of iteration number during the optimization process under different drone flight altitudes and uncertainties in the location of eavesdroppers.

[0059] Figure 4 A schematic diagram of the drone trajectory before and after optimization under different eavesdropper position error radii;

[0060] Figure 5 The graph shows the change in confidentiality rate as a function of the number of iterations during the optimization process under different eavesdropper location error radii.

[0061] Figure 6 This is a flowchart illustrating the algorithm execution of the present invention. Detailed Implementation

[0062] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0063] In the description of this invention, it should be understood that the terms "comprising" and "including" indicate the presence of the described features, integrals, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or collections thereof.

[0064] It should also be understood that the terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to limit the invention. As used in this specification and the appended claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms unless the context clearly indicates otherwise.

[0065] It should also be further understood that the term "and / or" as used in this specification and the appended claims refers to any combination and all possible combinations of one or more of the associated listed items, and includes such combinations. For example, A and / or B can represent three cases: A alone, A and B simultaneously, and B alone. Additionally, the character " / " in this document generally indicates that the preceding and following objects have an "or" relationship.

[0066] It should be understood that although terms such as first, second, third, etc., may be used in the embodiments of the present invention to describe the preset range, these preset ranges should not be limited to these terms. These terms are only used to distinguish the preset ranges from one another. For example, without departing from the scope of the embodiments of the present invention, the first preset range may also be referred to as the second preset range, and similarly, the second preset range may also be referred to as the first preset range.

[0067] Depending on the context, the word "if" as used here can be interpreted as "when," "when," "in response to determination," or "in response to detection." Similarly, depending on the context, the phrase "if determination" or "if detection (of the stated condition or event)" can be interpreted as "when determination," "in response to determination," "when detection (of the stated condition or event)," or "in response to detection (of the stated condition or event)."

[0068] The accompanying drawings illustrate various structural schematic diagrams according to embodiments disclosed in this invention. These drawings are not to scale, and some details have been enlarged for clarity, and some details may have been omitted. The shapes of the various regions and layers shown in the drawings, as well as their relative sizes and positional relationships, are merely exemplary and may deviate from reality due to manufacturing tolerances or technical limitations. Furthermore, those skilled in the art can design regions / layers with different shapes, sizes, and relative positions as needed.

[0069] Please see Figure 1 This invention first establishes a UAV-assisted downlink relay network communication system based on D2D technology to ensure the communication needs of ground users in special situations. In this downlink relay network system, ground users can either directly access the network through a single-hop communication link (as shown by the unidirectional solid arrow in the figure), or indirectly access the network through two communication links via other nearby ground users using D2D communication technology (as shown by the lightning bolt icon in the figure).

[0070] Please see Figure 6 The present invention discloses a method for trajectory and resource optimization in a UAV secure communication system, comprising the following steps:

[0071] S1. Initialize the UAV downlink relay network system and set the parameters of the communication link channel model;

[0072] The bandwidth W1 of the air-to-ground link, the bandwidth W2 of the ground link, the reference power gain ρ0 of the air-to-ground A2G channel at a distance of 1 meter, and the reference power gain ρ of the ground channel at a distance of 1 meter. d The transmit power P[n] of the UAV within any time slot n, and the maximum transmit power P of the UAV. max The average transmit power of the UAV, P avgTransmit power P of hybrid relay users d Gaussian white noise power σ 2 The fading coefficient k follows an exponential distribution. ij [n], the drone's flight altitude H, and the drone's maximum flight speed V. max Total number of users M, total number of time slots N, time slot length δ, and the projected coordinates w of the UAV's position on the ground. u The location coordinates w of ground user i i The location coordinates w of ground user j j The location coordinates of the eavesdropper w e The location coordinates w of the hybrid relay user r In any time slot n, the channel gain g between the drone and the eavesdropper. ue [n], the channel gain g between the hybrid relay user and the eavesdropper in any time slot n. re [n] represents the reachable rate R between the UAV and the authorized ground user within any time slot n. ui [n] represents the achievable rate R between the drone and the eavesdropper within any time slot n. ue [n], the achievable rate R between ground user i and ground user j within any time slot n. ij [n], the connection status x between the drone and ground user i during time interval n. i [n], the flag y indicating whether a D2D communication link can be established between ground user i and ground user j within any time slot n. ij [n] is a flag indicating whether ground user i is a hybrid relay user and whether it has successfully established a D2D communication link with D2D user j within any time slot n. ij [n] represents the communication security rate between the UAV and ground user i in any time slot n when the UAV communicates directly with ground user i. When a drone first communicates with a hybrid relay user, transmitting confidential information to the hybrid relay user, and then the hybrid relay user transmits the confidential information to a D2D user via the established D2D communication link, what is the confidentiality rate of this communication process within any time slot n? The overall security rate R of the UAV downlink relay network system s .

[0073] S2. In the UAV downlink relay network system established in step S1, parameters such as the UAV's flight altitude, ground user location, and error radius of the eavesdropper's location are set, and D2D pairing is performed using a random pairing method; the communication method for ground users to access the network is obtained.

[0074] S3. Initialize user scheduling, UAV transmission power and UAV flight trajectory, and initialize the iteration number of the UAV trajectory and resource optimization algorithm based on continuous convex approximation to 0. Set a threshold as the iteration termination condition of the optimization algorithm, and then perform optimization algorithm iteration. Record the change rate of the confidentiality rate of the ground user access network communication method obtained in step S2 after each iteration. When the change rate of the confidentiality rate is greater than or equal to the set threshold, the iteration will continue; otherwise, the iteration will be terminated.

[0075] S301, Initialize User Scheduling S k UAV transmission power P k and drone flight trajectory O k The algorithm iteration count k is initialized to 0, and a confidentiality rate change threshold ε is set as the iteration termination condition for the optimization algorithm.

[0076] S302, at a given UAV transmit power P k and drone flight trajectory O k The following optimizations will be made to user scheduling;

[0077] Calculate the reachability R from the UAV to the legitimate ground user in any time slot n. ui [n], the achievable speed R from the drone to the eavesdropper ue [n] and the reachable rate R between ground user i and ground user j ij [n], a flag indicating whether the UAV is serving ground user i at any time n. i [n] takes a value between 0 and 1, and in the same time slot, the drone serves at most one ground user, i.e., for x i [n] The sum of the numbers from i=1 to the total number of users M is less than or equal to 1, which serves as a constraint. The optimization objective is to maximize the overall security rate of the system, given the UAV's transmit power P. k and drone flight trajectory O k Based on this, an optimization process is performed to obtain the optimized user schedule S. k+1 And calculate the optimized overall system security rate R. s Finally, the security rate is processed. If the total security rate of the eavesdropping channel is greater than the total security rate of the legitimate channel at a certain moment, then communication between the UAV and the ground user at that moment is terminated, and the security rate at these moments is removed from the calculation of the overall system security rate. The optimized user scheduling S is then recorded. k+1 And the overall system security rate R s .

[0078] The achievable speed R between drones and ground users ui [n] is calculated as follows:

[0079]

[0080] The achievable rate R between drones and eavesdroppers ue [n] is calculated as follows:

[0081]

[0082] The reachable rate R between ground user i and ground user j ij [n] is calculated as follows:

[0083]

[0084] Where W1 represents the bandwidth of the air-to-ground link, W2 represents the bandwidth of the ground link, ρ0 represents the A2G (air-to-ground) channel reference power gain at a distance of 1 meter, and ρ d Let P[n] represent the ground channel reference power gain at a distance of 1 meter, and P[n] represent the UAV transmit power within any time slot n. d For the transmit power of hybrid relay users, σ 2 This represents the Gaussian white noise power, where H is the drone's flight altitude, and k is the power. ij [n] represents the fading coefficient, which follows an exponential distribution. u w represents the projected coordinates of the drone's position on the ground. i and w j Let w represent the location coordinates of ground user i and ground user j respectively. e Then, represents the location coordinates of the eavesdropper, ‖·‖ represents the Euclidean norm, and ‖w u -w i ‖ represents the Euclidean distance between the drone's position projected onto the ground and the ground user's position, ‖w e -w i ‖ and ||w i -w j || represent the Euclidean distance between the drone's projection on the ground and the eavesdropper's location, as well as the Euclidean distance between ground user i and ground user j, respectively.

[0085] There are two communication methods in this UAV relay communication network. One is that the UAV communicates directly with ground user i. In this case, the communication security rate between the UAV and ground user i can be expressed as:

[0086]

[0087] in

[0088] Another communication method involves establishing a D2D communication link. First, the UAV communicates with the hybrid relay user, transmitting confidential information to the hybrid relay user. Then, the hybrid relay user transmits the confidential information to the D2D user via the established D2D communication link. The confidentiality rate in this process can be expressed as...

[0089]

[0090] in

[0091]

[0092]

[0093]

[0094] The g here re [n] represents the channel gain between the hybrid relay user and the eavesdropper, ||w r -w e ‖ represents the Euclidean distance between the locations of the hybrid relay user and the eavesdropper.

[0095] In summary, the security level of this UAV downlink relay network is represented by R. s

[0096]

[0097] x ij [n] = x i [n]y ij [n]

[0098] Where y ij [n] is a flag indicating whether a D2D communication link can be established between ground user i and ground user j. A value of 1 indicates that a D2D communication link has been established, and 0 indicates that it has not been established; x i [n] represents the connection status between the UAV and ground user i within time slot n. A value of 1 indicates that the UAV is serving ground user i within time slot n; otherwise, x... i [n] = 0. x ij [n] = 1 indicates that the ground user i being served by the UAV is a hybrid relay user, and that user has successfully established a D2D communication link with D2D user j.

[0099] S303, on the given drone flight trajectory O k And the user schedule S obtained after optimization using step S302 k+1 The following optimizations were made to the drone's transmission power;

[0100] The UAV's transmit power P[n] at any given time n is less than or equal to the maximum transmit power P. max Furthermore, the result of summing the UAV transmit power at all times and dividing by the total number of time slots N is less than or equal to the average transmit power P. avg As a constraint, with the optimization objective of maximizing the overall security rate of the system, given the UAV flight trajectory O k And the user schedule S obtained after optimization using step S302 k+1 Based on this, an optimization process is performed on the UAV's transmission power to obtain the optimized UAV transmission power P. k+1 Then the achievable rate R was calculated. ui [n]、R ue [n] and R ij [n], and calculate the overall security rate of the system. Finally, process the security rate: if the total security rate of the eavesdropping channel is greater than the total security rate of the legitimate channel at a certain moment, then remove the security rate of those moments from the calculation of the overall system security rate, and record the optimized UAV transmit power P. k+1 And the overall system security rate R s .

[0101] S304, The user schedule S obtained after optimization using step S302 k+1 The UAV transmit power P obtained after optimization using step S303 k+1 The flight path of the drone will be optimized.

[0102] Within a service cycle, the start and end points of the drone's flight trajectory are the same, and the square of the drone's flight distance at any given time is less than or equal to the drone's maximum flight speed V. max The square of the product of the time slot length δ and two constraints on the slack variables are used as constraints to maximize the overall security rate of the system as the optimization objective. The user scheduling S obtained after optimization using step S302 is then used. k+1 The UAV transmit power P obtained after optimization using step S303 is... k+1 Based on this, an optimization process is performed on the drone's flight trajectory to obtain the optimized drone flight trajectory O. k+1 Then the achievable rate R was calculated. ui [n]、R ue [n] and R ij [n], and calculate the overall security rate of the system; finally, process the security rate. If the total security rate of the eavesdropping channel is greater than the total security rate of the legitimate channel at a certain moment, then remove the security rate of these moments from the calculation of the overall security rate of the system, and record the optimized UAV flight trajectory O. k+1 And the overall system security rate R s .

[0103] S305. Increment the iteration count k by 1. Based on the user scheduling S obtained after optimization in S302, S303, and S304... k+1 UAV transmission power P k+1 and drone flight trajectory O k+1 Overall security rate R of the computing system s And calculate the rate of change of the confidentiality rate ΔR. s When the rate of change in confidentiality ΔR s When the value is greater than or equal to a pre-set threshold ε, the S obtained in this iteration of optimization is... k+1 P k+1 and O k+1 S is given in the next iteration. k P k and O k Continue executing step S302 to perform the iterative optimization process; otherwise, terminate the iterative optimization process.

[0104] Step S4 and Step S3 optimization algorithm iterations end after multiple iterations, resulting in a UAV flight trajectory and resource allocation scheme that can significantly improve the system's security performance.

[0105] In another embodiment of the present invention, a trajectory and resource optimization system for a UAV safe communication system is provided. This system can be used to implement the above-mentioned trajectory and resource optimization method for a UAV safe communication system. Specifically, the UAV safe communication system trajectory and resource optimization system includes an initial module, a pairing module, an iteration module, and an optimization module.

[0106] The initial module initializes the UAV downlink relay network system and sets the parameters of the communication link channel model.

[0107] The pairing module sets the error radius of the UAV's flight altitude, ground user location, and eavesdropper location in the UAV downlink relay network system established by the initial module, and performs D2D pairing in a random pairing manner to obtain the communication method for ground users to access the network.

[0108] The iteration module initializes user scheduling, UAV transmission power, and UAV flight trajectory, and initializes the iteration count of the UAV trajectory and resource optimization algorithm based on continuous convex approximation to 0. A threshold is set as the iteration termination condition for the optimization algorithm. The optimization algorithm is then iterated, and the change rate of the confidentiality rate of the ground user access network communication method obtained by the pairing module after each iteration is recorded. If the change rate of the confidentiality rate is greater than or equal to the set threshold, the iteration continues; otherwise, the iteration exits.

[0109] The optimization module and the iteration module optimize the algorithm. After the algorithm completes the iteration, the UAV flight trajectory and resource allocation scheme are obtained, thus realizing trajectory and resource optimization.

[0110] In another embodiment of the present invention, a terminal device is provided, comprising a processor and a memory. The memory stores a computer program, which includes program instructions. The processor executes the program instructions stored in the computer storage medium. The processor may be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. It is the computing and control core of the terminal, suitable for implementing one or more instructions, specifically suitable for loading and executing one or more instructions to achieve corresponding method flows or corresponding functions. The processor described in this embodiment of the present invention can be used for the operation of trajectory and resource optimization methods in UAV safety communication systems, including:

[0111] Initialize the UAV downlink relay network system and set the parameters of the communication link channel model. Within the UAV downlink relay network system, set the error radii for the UAV's flight altitude, ground user location, and eavesdropper location, and perform D2D pairing using random pairing to obtain the communication method for ground users accessing the network. Initialize user scheduling, UAV transmit power, and UAV flight trajectory, and initialize the iteration count of the UAV trajectory and resource optimization algorithm based on continuous convex approximation to 0. Set a threshold as the iteration termination condition for the optimization algorithm, and then iterate the optimization algorithm. Record the rate of change in the security level of the ground user accessing the network communication method after each iteration. If the rate of change in the security level is greater than or equal to the set threshold, continue iterating; otherwise, exit the iteration. After the optimization algorithm iteration is complete, obtain the UAV flight trajectory and resource allocation scheme, achieving trajectory and resource optimization.

[0112] In another embodiment of the present invention, a storage medium is provided, specifically a computer-readable storage medium (memory). This computer-readable storage medium is a memory device in a terminal device used to store programs and data. It is understood that the computer-readable storage medium here can include both the built-in storage medium in the terminal device and extended storage media supported by the terminal device. The computer-readable storage medium provides storage space that stores the terminal's operating system. Furthermore, this storage space also stores one or more instructions suitable for loading and execution by a processor. These instructions can be one or more computer programs (including program code). It should be noted that the computer-readable storage medium here can be high-speed RAM or non-volatile memory, such as at least one disk storage device.

[0113] One or more instructions stored in a computer-readable storage medium can be loaded and executed by a processor to implement the corresponding steps of the UAV safety communication system trajectory and resource optimization method in the above embodiments; one or more instructions in the computer-readable storage medium are loaded and executed by the processor in the following steps:

[0114] Initialize the UAV downlink relay network system and set the parameters of the communication link channel model. Within the UAV downlink relay network system, set the error radii for the UAV's flight altitude, ground user location, and eavesdropper location, and perform D2D pairing using random pairing to obtain the communication method for ground users accessing the network. Initialize user scheduling, UAV transmit power, and UAV flight trajectory, and initialize the iteration count of the UAV trajectory and resource optimization algorithm based on continuous convex approximation to 0. Set a threshold as the iteration termination condition for the optimization algorithm, and then iterate the optimization algorithm. Record the rate of change in the security level of the ground user accessing the network communication method after each iteration. If the rate of change in the security level is greater than or equal to the set threshold, continue iterating; otherwise, exit the iteration. After the optimization algorithm iteration is complete, obtain the UAV flight trajectory and resource allocation scheme, achieving trajectory and resource optimization.

[0115] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention.

[0116] Please see Figure 2 This diagram illustrates the optimized drone flight trajectories under varying drone flight altitudes and uncertainties surrounding the eavesdropper's position. The elliptical curves represent the original drone flight trajectory set by the algorithm, while the irregular curves with different markings represent the optimized drone flight trajectories at different flight altitudes. Solid lines indicate the case without considering the eavesdropper's position uncertainty, while dashed lines indicate the case considering it. The dashed circle centered on the eavesdropper's position represents the error radius of the eavesdropper's position. The legend illustrates the parameter settings for different schemes, where H represents the drone flight altitude, Q represents the error radius of the eavesdropper's position, and Q = 0m indicates that the eavesdropper's position is accurate and there is no error.

[0117] Please see Figure 3 It was shown in Figure 2 The changes in system security rate during the optimization process of each scheme are shown.

[0118] Please see Figure 4 This diagram illustrates the optimized drone flight trajectories under different eavesdropper position error radii. The elliptical curve represents the original drone flight trajectory set by the algorithm. Irregular curves with different markings represent the optimized drone flight trajectories with different eavesdropper error radii. Solid lines represent the case where eavesdropper position uncertainty is not considered, i.e., the error radius is 0. Dashed lines with different markings represent cases considering different eavesdropper position error radii. The dashed circles with different radii centered on the eavesdropper position represent different eavesdropper position error radii. In the legend, Q represents the eavesdropper position error radius; Q = 0m indicates that the eavesdropper position is accurate and there is no error.

[0119] Please see Figure 5 It was shown in Figure 4 The changes in system security rate during the optimization process of each scheme are shown.

[0120] Experimental simulation results demonstrate the effectiveness and robustness of the algorithm employed in this invention, showing that it provides high security for the communication system even when the location of the eavesdropper is uncertain. Furthermore, the algorithm remains applicable even when the drone's flight altitude changes.

[0121] In summary, this invention designs a secure communication scheme for UAV-assisted communication networks based on D2D multi-hop communication networks. It incorporates consideration of the uncertainty of the eavesdropper's location. After optimization using the algorithm employed in this invention, the overall system security rate in scenarios with uncertain eavesdropper locations is very close to that in scenarios with determined eavesdropper locations. This demonstrates the effectiveness and robustness of this method, proving that it can provide high security performance for the communication system even when the eavesdropper's location is uncertain.

[0122] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is merely an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit. Furthermore, the specific names of the functional units and modules are only for easy differentiation and are not intended to limit the scope of protection of this application. The specific working process of the units and modules in the above system can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0123] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0124] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0125] In the embodiments provided by this invention, it should be understood that the disclosed devices / terminals and methods can be implemented in other ways. For example, the device / terminal embodiments described above are merely illustrative. For instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0126] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0127] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0128] If the integrated module / unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or device capable of carrying the computer program code, recording media, USB flash drives, portable hard drives, magnetic disks, optical disks, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc. It should be noted that the content included in the computer-readable medium can be appropriately added or removed according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable media do not include electrical carrier signals and telecommunication signals.

[0129] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0130] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0131] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0132] The above content is only for illustrating the technical concept of the present invention and should not be construed as limiting the scope of protection of the present invention. Any modifications made to the technical solution based on the technical concept proposed in this invention shall fall within the scope of protection of the claims of this invention.

Claims

1. A method for trajectory and resource optimization in a UAV secure communication system, characterized in that, Includes the following steps: S1. Initialize the UAV downlink relay network system and set the parameters of the communication link channel model. The specific parameters of the communication link channel model include: Bandwidth of air-to-ground link terrestrial link bandwidth Air-to-ground A2G channel reference power gain at a distance of 1 meter Ground channel reference power gain at a distance of 1 meter Arbitrary time slot Internal UAV transmission power Maximum transmit power of drones Average transmit power of drones Transmit power of hybrid relay users Gaussian white noise power The fading coefficient follows an exponential distribution. The flight altitude of the drone Maximum flight speed of drones Total number of users Total number of time slots Time slot length The projected coordinates of the drone's position on the ground The location coordinates of ground user i The location coordinates of ground user j Location coordinates of the eavesdropper Location coordinates of hybrid relay users In any time slot Internally, the channel gain between the drone and the eavesdropper. In any time slot Internally, the channel gain between hybrid relay users and eavesdroppers. In any time slot Within, the reachability rate between drones and legitimate ground users In any time slot Inside, the reachability rate between drones and eavesdroppers In any time slot Within, the reachable rate between ground user i and ground user j During the time gap Internally, the connection status between the drone and ground user i In any time slot Within, the flag indicating whether a D2D communication link can be established between ground user i and ground user j. Indicates any time slot Internally, the flag indicating whether ground user i is a hybrid relay user and whether it has successfully established a D2D communication link with D2D user j. When the drone communicates directly with ground user i, in any time slot Internally, the confidentiality rate of communication between the drone and the ground user i When the drone first communicates with the hybrid relay user, transmitting confidential information to the hybrid relay user, and then the hybrid relay user transmits the confidential information to the D2D user through the established D2D communication link, in any time slot... Within this communication process, the confidentiality rate is... Overall security rate of UAV downlink relay network system ; S2. In the UAV downlink relay network system established in step S1, the error radius of the UAV's flight altitude, ground user location, and eavesdropper location is set, and D2D pairing is performed using a random pairing method to obtain the communication method for ground users to access the network. S3. Initialize user scheduling, UAV transmit power, and UAV flight trajectory. Initialize the iteration count of the UAV trajectory and resource optimization algorithm based on continuous convex approximation to 0. Set a threshold as the termination condition for the optimization algorithm iteration. Then, iterate the optimization algorithm, recording the rate of change in the security level of the ground user access network communication method obtained in step S2 after each iteration. Continue iteration when the rate of change in the security level is greater than or equal to the set threshold; otherwise, exit the iteration. The specific iteration process for the optimization algorithm is as follows: S301, initialize user scheduling S k , the launch power P of the unmanned aerial vehicle k , and the flight trajectory O of the unmanned aerial vehicle k , initialize the iteration number k of the algorithm to 0, and set a privacy rate change rate threshold value ε as an iteration end condition of the optimization algorithm; S302, at a given UAV transmit power P k and drone flight trajectory O k Below, at any time Flag indicating whether the drone serves ground user i Values ​​between 0 and 1, and the fact that a drone can only serve one ground user in the same time slot, i.e. From i=1 to Using the constraint that the summation result is less than or equal to 1, the user schedule is optimized to obtain the optimized user schedule S. k+1 Specifically: Calculate in any time slot Accessibility rate from internal drones to authorized ground users The achievable speed from drones to eavesdroppers and the reachable rate between ground user i and ground user j At any time Flag indicating whether the drone serves ground user i Values ​​between 0 and 1, and the fact that a drone can only serve one ground user in the same time slot, i.e. From i=1 to The summation result is less than or equal to 1 as a constraint, with the optimization objective being to maximize the overall security rate of the system, given the UAV's transmit power P. k and drone flight trajectory O k Based on this, an optimization process is performed to obtain the optimized user schedule S. k+1 And calculate the overall security rate of the optimized system. Finally, the security rate is processed. If the total security rate of the eavesdropping channel is greater than that of the legitimate channel, communication between the UAV and the ground user is suspended at the corresponding time. The security rates at these times are removed from the calculation of the overall system security rate, and the optimized user scheduling S is recorded. k+1 and overall system security rate ; S303, on the given drone flight trajectory O k The user schedule S obtained after optimization in step S302 k+1 Under the condition, at any time Internal UAV transmission power Less than or equal to maximum transmit power And greater than or equal to 0, and summing the drone's transmit power over all times and then dividing by the total number of times. The result is less than or equal to the average transmit power. As a constraint, the UAV's transmit power is optimized to obtain the optimized UAV transmit power P. k+1 Specifically: At any time Internal UAV transmission power Less than or equal to maximum transmit power And greater than or equal to 0, and the sum of the drone's transmit power at all times and then divided by the total number of times. The result is less than or equal to the average transmit power. As a constraint, with the optimization objective of maximizing the overall security rate of the system, given the UAV flight trajectory O k And the user schedule S obtained after optimization using step S302 k+1 Based on this, an optimization process is performed on the UAV's transmission power to obtain the optimized UAV transmission power P. k+1 Then the achievable rates were calculated separately. , as well as The overall security rate of the system is calculated. Finally, the security rate is processed by removing instances where the overall security rate of the eavesdropping channel is greater than that of the legitimate channel. The optimized UAV transmit power P is then recorded. k+1 and overall system security rate ; S304. Utilize the user scheduling S obtained after optimization in step S302. k+1 The UAV transmit power P obtained after optimization in step S303 k+1 The drone flight trajectory is optimized using the following constraints: the start and end points of the drone's flight trajectory are the same within a service cycle; the square of the drone's flight distance at any given time is less than or equal to the square of the product of the drone's maximum flight speed and the time slot length; and two constraints on slack variables. The optimized drone flight trajectory O is obtained. k+1 Specifically: Using constraints such as the same start and end point of the UAV flight trajectory within a service cycle, the square of the UAV flight distance at any time being less than or equal to the square of the product of the UAV's maximum flight speed and the time slot length, and two constraints on slack variables, the optimization objective is to maximize the overall security rate of the system. The user scheduling S obtained after optimization using step S302 is then optimized. k+1 The UAV transmit power P obtained after optimization using step S303 is... k+1 Based on this, an optimization process is performed on the drone's flight trajectory to obtain the optimized drone flight trajectory O. k+1 Then the achievable rates were calculated separately. , as well as The overall security rate of the system is calculated. Finally, the security rate is processed by removing instances where the total security rate of the eavesdropping channel is greater than that of the legitimate channel. The optimized UAV flight trajectory O is then recorded. k+1 and overall system security rate ; S305. Increment the iteration count k by 1, and optimize the user schedule S based on the result obtained in step S302. k+1 The UAV transmit power P obtained after S303 optimization k+1 The UAV flight trajectory O obtained after optimization with S304 k+1 Overall security rate of computing system And calculate the rate of change of the confidentiality rate. When the rate of change in confidentiality Greater than or equal to a preset threshold At that time, the S obtained from this iteration optimization will be... k+1 P k+1 and O k+1 S is given in the next iteration. k P k and O k Continue executing step S302 to perform the iterative optimization process; otherwise, terminate the iterative optimization process. After the optimization algorithm iterations in steps S4 and S3 are completed, the UAV flight trajectory and resource allocation scheme are obtained, thus achieving trajectory and resource optimization.

2. The method for optimizing the trajectory and resources of a UAV secure communication system according to claim 1, characterized in that, In any time slot Within, the reachability rate between drones and legitimate ground users The calculation is as follows: achievable speed between drones and eavesdroppers The calculation is as follows: The reachable rate between ground user i and ground user j The calculation is as follows: in, This indicates the bandwidth of the air-to-ground link. This indicates the bandwidth of the terrestrial link. This represents the A2G (air-to-ground) channel reference power gain at a distance of 1 meter. This represents the ground channel reference power gain at a distance of 1 meter. For any time slot Internal UAV transmission power, For the transmit power of hybrid relay users, This represents the power of Gaussian white noise. The flight altitude of the drone. The fading coefficient follows an exponential distribution. This represents the projected coordinates of the drone's position on the ground. and These represent the location coordinates of ground user i and ground user j, respectively. This indicates the location coordinates of the eavesdropper. Describes the Euclidean norm. This represents the Euclidean distance between the drone's position projected onto the ground and the ground user's position. and Let i represent the Euclidean distance between the drone's position projected onto the ground and the eavesdropper's position, and the Euclidean distance between ground user i and ground user j, respectively. In UAV downlink relay networks, the system's security level is... Represented as: in, This is a flag indicating whether a D2D communication link can be established between ground user i and ground user j. Indicates a time gap The connection status between the drone and the ground user i This indicates that the ground user i being served by the drone is a hybrid relay user, and that this user has successfully established a D2D communication link with D2D user j. In the case where the UAV communicates directly with ground user i, the communication security rate between the UAV and ground user i is... To ensure that when a drone first communicates with a hybrid relay user, transmitting confidential information to the hybrid relay user, and then the hybrid relay user transmits the confidential information to the D2D user via the established D2D communication link, in any time slot... Internally, the confidentiality rate of the communication process.

3. A trajectory and resource optimization system for a UAV safe communication system, characterized in that, include: The initial module initializes the UAV downlink relay network system and sets the parameters of the communication link channel model. The specific parameters of the communication link channel model include: Bandwidth of air-to-ground link terrestrial link bandwidth Air-to-ground A2G channel reference power gain at a distance of 1 meter Ground channel reference power gain at a distance of 1 meter Arbitrary time slot Internal UAV transmission power Maximum transmit power of drones Average transmit power of drones Transmit power of hybrid relay users Gaussian white noise power The fading coefficient follows an exponential distribution. The flight altitude of the drone Maximum flight speed of drones Total number of users Total number of time slots Time slot length The projected coordinates of the drone's position on the ground The location coordinates of ground user i The location coordinates of ground user j Location coordinates of the eavesdropper Location coordinates of hybrid relay users In any time slot Internally, the channel gain between the drone and the eavesdropper. In any time slot Internally, the channel gain between hybrid relay users and eavesdroppers. In any time slot Within, the reachability rate between drones and legitimate ground users In any time slot Inside, the reachability rate between drones and eavesdroppers In any time slot Within, the reachable rate between ground user i and ground user j During the time gap Internally, the connection status between the drone and ground user i In any time slot Within, the flag indicating whether a D2D communication link can be established between ground user i and ground user j. Indicates any time slot Internally, the flag indicating whether ground user i is a hybrid relay user and whether it has successfully established a D2D communication link with D2D user j. When the drone communicates directly with ground user i, in any time slot Internally, the confidentiality rate of communication between the drone and the ground user i When the drone first communicates with the hybrid relay user, transmitting confidential information to the hybrid relay user, and then the hybrid relay user transmits the confidential information to the D2D user through the established D2D communication link, in any time slot... Within this communication process, the confidentiality rate is... Overall security rate of UAV downlink relay network system ; The pairing module sets the error radius of the UAV's flight altitude, ground user location, and eavesdropper location in the UAV downlink relay network system established by the initial module, and performs D2D pairing in a random pairing manner to obtain the communication method for ground users to access the network. The iterative module initializes user scheduling, UAV transmit power, and UAV flight trajectory. It also initializes the iteration count of the UAV trajectory and resource optimization algorithm based on continuous convex approximation to 0. A threshold is set as the termination condition for the optimization algorithm iteration. The optimization algorithm then iterates, recording the change rate of the security rate of the ground user access network communication method obtained by the pairing module after each iteration. Iteration continues when the change rate of the security rate is greater than or equal to the set threshold; otherwise, the iteration exits. Specifically, the optimization algorithm iteration is as follows: Initialize user scheduling S k UAV transmission power P k and drone flight trajectory O k The algorithm iteration count k is initialized to 0, and a confidentiality rate change threshold ε is set as the iteration termination condition for the optimization algorithm. Given the drone's transmit power P k and drone flight trajectory O k Below, at any time Flag indicating whether the drone serves ground user i Values ​​between 0 and 1, and the fact that a drone can only serve one ground user in the same time slot, i.e. From i=1 to Using the constraint that the summation result is less than or equal to 1, the user schedule is optimized to obtain the optimized user schedule S. k+1 Specifically: Calculate in any time slot Accessibility rate from internal drones to authorized ground users The achievable speed from drones to eavesdroppers and the reachable rate between ground user i and ground user j At any time Flag indicating whether the drone serves ground user i Values ​​between 0 and 1, and the fact that a drone can only serve one ground user in the same time slot, i.e. From i=1 to The summation result is less than or equal to 1 as a constraint, with the optimization objective being to maximize the overall security rate of the system, given the UAV's transmit power P. k and drone flight trajectory O k Based on this, an optimization process is performed to obtain the optimized user schedule S. k+1 And calculate the overall security rate of the optimized system. Finally, the security rate is processed. If the total security rate of the eavesdropping channel is greater than that of the legitimate channel, communication between the UAV and the ground user is suspended at the corresponding time. The security rates at these times are removed from the calculation of the overall system security rate, and the optimized user scheduling S is recorded. k+1 and overall system security rate ; Given the drone's flight trajectory O k And the optimized user schedule S k+1 Under the condition, at any time Internal UAV transmission power Less than or equal to maximum transmit power And greater than or equal to 0, and summing the drone's transmit power over all times and then dividing by the total number of times. The result is less than or equal to the average transmit power. As a constraint, the UAV's transmit power is optimized to obtain the optimized UAV transmit power P. k+1 Specifically: At any time Internal UAV transmission power Less than or equal to maximum transmit power And greater than or equal to 0, and the sum of the drone's transmit power at all times and then divided by the total number of times. The result is less than or equal to the average transmit power. As a constraint, with the optimization objective of maximizing the overall security rate of the system, given the UAV flight trajectory O k And the optimized user schedule S k+1 Based on this, an optimization process is performed on the UAV's transmission power to obtain the optimized UAV transmission power P. k+1 Then the achievable rates were calculated separately. , as well as The overall security rate of the system is calculated. Finally, the security rate is processed by removing instances where the overall security rate of the eavesdropping channel is greater than that of the legitimate channel. The optimized UAV transmit power P is then recorded. k+1 and overall system security rate ; Using the optimized user schedule S k+1 And the optimized UAV transmit power P k+1 The drone flight trajectory is optimized using the following constraints: the start and end points of the drone's flight trajectory are the same within a service cycle; the square of the drone's flight distance at any given time is less than or equal to the square of the product of the drone's maximum flight speed and the time slot length; and two constraints on slack variables. The optimized drone flight trajectory O is obtained. k+1 Specifically: Using the constraints that the start and end points of the UAV flight trajectories are the same within a service cycle, that the square of the UAV flight distance at any given time is less than or equal to the square of the product of the UAV's maximum flight speed and the time slot length, and two constraints on slack variables as the optimization objective, the overall security rate of the system is maximized. The optimized user scheduling S is then used... k+1 and the optimized UAV transmit power P k+1 Based on this, an optimization process is performed on the drone's flight trajectory to obtain the optimized drone flight trajectory O. k+1 Then the achievable rates were calculated separately. , as well as The overall security rate of the system is calculated. Finally, the security rate is processed by removing instances where the total security rate of the eavesdropping channel is greater than that of the legitimate channel. The optimized UAV flight trajectory O is then recorded. k+1 and overall system security rate ; Increment the iteration count k by 1, and then use the optimized user schedule S. k+1 The optimized UAV transmit power P k+1 And the optimized UAV flight trajectory O k+1 Overall security rate of computing system And calculate the rate of change of the confidentiality rate. When the rate of change in confidentiality Greater than or equal to a preset threshold At that time, the S obtained from this iteration optimization will be... k+1 P k+1 and O k+1 S is given in the next iteration. k P k and O k Continue executing step S302 to perform the iterative optimization process; otherwise, terminate the iterative optimization process. The optimization module and the iteration module optimize the algorithm. After the algorithm completes the iteration, the UAV flight trajectory and resource allocation scheme are obtained, thus realizing trajectory and resource optimization.

4. The trajectory and resource optimization system for a UAV secure communication system according to claim 3, characterized in that, In any time slot Within, the reachability rate between drones and legitimate ground users The calculation is as follows: achievable speed between drones and eavesdroppers The calculation is as follows: The reachable rate between ground user i and ground user j The calculation is as follows: in, This indicates the bandwidth of the air-to-ground link. This indicates the bandwidth of the terrestrial link. This represents the A2G (air-to-ground) channel reference power gain at a distance of 1 meter. This represents the ground channel reference power gain at a distance of 1 meter. For any time slot Internal UAV transmission power, For the transmit power of hybrid relay users, This represents the power of Gaussian white noise. The flight altitude of the drone. The fading coefficient follows an exponential distribution. This represents the projected coordinates of the drone's position on the ground. and These represent the location coordinates of ground user i and ground user j, respectively. This indicates the location coordinates of the eavesdropper. Describes the Euclidean norm. This represents the Euclidean distance between the drone's position projected onto the ground and the ground user's position. and Let i represent the Euclidean distance between the drone's position projected onto the ground and the eavesdropper's position, and the Euclidean distance between ground user i and ground user j, respectively. In UAV downlink relay networks, the system's security level is... Represented as: in, This is a flag indicating whether a D2D communication link can be established between ground user i and ground user j. Indicates a time gap The connection status between the drone and the ground user i This indicates that the ground user i being served by the drone is a hybrid relay user, and that this user has successfully established a D2D communication link with D2D user j. In the case where the UAV communicates directly with ground user i, the communication security rate between the UAV and ground user i is... To ensure that when a drone first communicates with a hybrid relay user, transmitting confidential information to the hybrid relay user, and then the hybrid relay user transmits the confidential information to the D2D user via the established D2D communication link, in any time slot... Internally, the confidentiality rate of the communication process.

5. A computer-readable storage medium for storing one or more programs, characterized in that, The one or more programs include instructions that, when executed by a computing device, cause the computing device to perform the method of claim 1 or 2.

6. A computing device, characterized in that, include: One or more processors, a memory, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs including steps for performing the method of claim 1 or 2.

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