Secure communication method based on artificial noise in unmanned aerial vehicle NOMA network

Abstract

The invention discloses a secure communication method based on artificial noise in an unmanned aerial vehicle NOMA network. The communication process has two time slots. In a first time slot, a base station adopts an NOMA mechanism to send a signal to an unmanned aerial vehicle, meanwhile, the unmanned aerial vehicle selects one antenna to send an artificial noise signal to interfere with an untrusted remote user, the remaining antennas receive the signal, and a near user also sends the artificial noise signal; in a second time slot, the unmanned aerial vehicle adds the artificial noise signal and the near user signal of the first time slot by means of exclusive OR, then superposes the obtained signal and the far user signal by means of an NOMA mechanism, and finally reselects one antenna to send the superposed signal; then the NOMA user obtains a corresponding signal to interference plus noise ratio or a signal to noise ratio according to the received signal, and calculates a system outage probability and an eavesdropping probability; the method can effectively weaken the eavesdropping capability of the untrusted user, basically does not affect the untrusted user to receive the own message, and helps to solve the problem of potential safety hazards in an actual unmanned aerial vehicle cooperative NOMA network communication scene.

Description

Technical Field

[0001] The present invention belongs to the technical field of wireless communication physical layer security, and in particular to an artificial noise method used to counter untrusted users in a cooperative non-orthogonal multiple access (NOMA) network of unmanned aerial vehicles. Background Art

[0002] With the development of wireless network technology, the number of network users and the amount of data carried by the network are growing exponentially, and network spectrum resources are becoming increasingly scarce. NOMA technology allows multiple users to share the same spectrum resources at the same time, so NOMA technology can effectively alleviate the shortage of wireless communication spectrum resources and improve the utilization rate of wireless communication network spectrum resources. When drones are used in wireless communications, they have attracted widespread attention from scholars at home and abroad for their easy and flexible deployment, low operating costs, and stable transmission channel performance. In wireless communications, drones can be flexibly deployed in suburbs and rural areas as base stations or relay nodes, which can effectively expand the coverage of communication signals. Obviously, applying NOMA technology to drone communications can combine the advantages of NOMA technology and drone communications, and further improve the performance of drone communication networks.

[0003] Although drone communication networks using NOMA technology have many advantages, the broadcast characteristics of radio signals make drone communications vulnerable to eavesdropping attacks. Unlike traditional cryptographic technology, physical layer security technology uses the physical characteristics of signals and wireless channels to effectively combat eavesdropping attacks on wireless networks. Therefore, artificial noise technology is a very useful technology to combat eavesdropping attacks. However, when users in the drone NOMA network are untrustworthy, if artificial noise is used to weaken the eavesdropper, then the artificial noise will also affect the untrustworthy user's ability to receive their own messages. If the artificial noise is weakened, the untrustworthy user's eavesdropping ability will be enhanced. Therefore, using artificial noise technology to combat untrustworthy users in the drone NOMA network faces a dilemma. Summary of the invention

[0004] Purpose of the invention: The purpose of the present invention is to provide a secure communication method based on artificial noise in a drone NOMA network. The secure communication scheme designed by the present invention based on artificial noise and relay cooperation strategy, while realizing secure communication between ground base stations and trusted near users, hardly affects the efficient reception of their own messages by untrusted far users, that is, hardly affects the communication reliability of untrusted far users. Under the premise of ensuring secure communication of trusted users in the drone NOMA network, it hardly affects the decoding of their own messages by untrusted users.

[0005] Technical solution: A secure communication method based on artificial noise in a drone NOMA network of the present invention is applied to a collaborative NOMA communication system in which a drone is a relay node and there are untrusted users. The system includes a ground base station, a drone equipped with multiple antennas, a trusted near user equipped with two antennas, and an untrusted far user equipped with a single antenna. The secure communication method includes the following steps:

[0006] Step 1: In the first time slot, the base station as the source uses the NOMA mechanism to superimpose and send the signal. The drone relay node selects an antenna to send an artificial noise signal, and the reliable nearby user also sends another artificial noise signal at the same time.

[0007] Step 2: The drone and NOMA user calculate the signal-to-interference-noise ratio based on the received signal;

[0008] Step 3: If the drone relay node fails to decode the source signal, it is directly determined that the communication is interrupted and jumps to step 5; if the drone relay node successfully decodes the source signal, in the second time slot, the drone relay node XORs the artificial noise of the first time slot and the decoded near-user signal, and then uses the NOMA mechanism to superimpose the signal and send it to the NOMA user;

[0009] Step 4: The NOMA user calculates the signal-to-interference-plus-noise ratio and the signal-to-noise ratio based on the received signal;

[0010] Step 5: The trusted near user and the untrusted far user calculate the corresponding interruption probability and eavesdropping probability respectively according to the obtained signal-to-interference-plus-noise ratio and signal-to-noise ratio.

[0011] Furthermore, step 1 is as follows: the base station as the signal source adopts the NOMA mechanism to linearly superimpose the signals x1 and x2 to obtain Then x is sent, and the drone relay node selects an antenna to send the artificial noise signal x J , it is believed that the nearby user also sends another artificial noise signal x J1 Interference with untrusted distant users.

[0012] Furthermore, step 2 is specifically as follows: the signal-to-interference-noise ratios of the decoded signals x2 and x1 of the drone relay node in the first time slot are respectively:

[0013]

[0014] Among them, Ψ is the set of N antennas of the drone, is the set of N-1 antennas remaining after antenna selection, Indicates the source to The column vector composed of the instantaneous channel state information of the antennas in, is the precoding vector based on the null space technique, is the vector transpose symbol; P S is the source signal transmission power, is the noise power at any receiving antenna of the drone, γ rr is the residual self-interference of the drone node; NOMA users need to obtain the artificial noise signal x sent by the drone relay node when decoding their own signals J , the credible near user and the untrusted far user decode the artificial noise signal x J The signal-to-interference-noise ratios are:

[0015]

[0016] in, and are the instantaneous channel state information from the i-th antenna of the drone to the near user and the far user, respectively. is the instantaneous channel state information from near users to far users, is the residual self-interference signal near the user; P r1 is the power of the artificial noise signal sent by the drone in the first time slot, and are the noise powers of near users and far users respectively.

[0017] Furthermore, the signal-to-noise ratio calculation process of the first time slot drone relay node decoding signals x1 and x2, and the NOMA user decoding artificial noise signal x J The signal-to-interference-noise ratio calculation process is:

[0018] First, the drone as a relay node selects an antenna from the N antenna set Ψ to send an artificial noise signal x J , the antenna selection rule is:

[0019]

[0020] The remaining N-1 antennas form a set of Used to receive the signal sent by the source, and the artificial noise signal x can be sent by the nearby user at the same time J1 Interference is performed on untrusted distant users; thus the signal received by the drone is:

[0021]

[0022] in, represents the column vector composed of additive Gaussian white noise of each receiving signal antenna at the drone relay node, is the precoding vector based on the null space technology, which is used to eliminate the artificial noise signal x at the drone relay node J1 ,satisfy Thus, the signal-to-interference-noise ratio is calculated and Because the signal-to-interference-noise ratio and Maximization is equivalent to Maximization of The following optimization problem:

[0023]

[0024] The received signals of the trusted near user and the untrusted far user are:

[0025]

[0026] in, and denote the additive Gaussian white noise at the trusted near user and the untrusted far user respectively; because the secure communication scheme is based on the relay cooperation strategy and XOR operation, the final NOMA user needs to use the artificial noise signal x J Obtain the source message, so you need to calculate x J According to the signal received by the NOMA user, the decoded x J The signal-to-interference-noise ratio is and

[0027] Furthermore, step 3 is as follows: if the drone relay node fails to decode the source signal, the communication is directly determined to be interrupted and the process goes to step 5; if the drone relay node successfully decodes the source signal, the second time slot converts x1 and x J XOR addition Then adopt NOMA mechanism Linear superposition with x2 gives Finally, x r Sent to NOMA users.

[0028] Further, the second time slot, x2 and The signal-to-interference-noise ratio and signal-to-noise ratio are:

[0029]

[0030] in, is the instantaneous channel state information from the kth antenna of the drone to the near user in the second time slot, P r2 is the signal transmission power of the drone in the second time slot; the signal-to-interference-noise ratio of the decoded signal x2 of the untrusted distant user is:

[0031]

[0032] in, is the instantaneous channel state information from the kth antenna of the drone to the untrusted remote user in the second time slot; the untrusted remote user, as an eavesdropper, has strong eavesdropping ability, so its decoding The signal-to-noise ratio is:

[0033]

[0034] Further, step 4 is specifically as follows: the credible user receives the received signal Calculate the signal-to-interference-noise ratio Untrusted remote users receive signals based on Calculated signal-to-noise ratio If an untrusted user wants to eavesdrop on x1, he needs to calculate the signal-to-noise ratio. Combined with the signal-to-interference-noise ratio Decode x1.

[0035] Furthermore, step 5 is specifically as follows:

[0036] The probability of reliable user interruption is:

[0037]

[0038] The probability that a trusted user is eavesdropped is:

[0039]

[0040] in, and are the thresholds for decoding signals x1 and x2, r1 and r2 are the information rate thresholds for signals x1 and x2, is the threshold value for an untrusted user to eavesdrop on the nearby user signal x1, r e is the eavesdropping information rate threshold; the interruption probability of untrusted remote users is:

[0041]

[0042] The present invention also discloses a computer device, comprising a memory, a processor and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of the method of the present invention.

[0043] The present invention also discloses a computer-readable storage medium on which a computer program / instruction is stored. When the computer program / instruction is executed by a processor, the steps of the method of the present invention are implemented.

[0044] Beneficial effects: Compared with the prior art, the present invention has the following significant advantages:

[0045] 1. Combining NOMA technology with drone communications can not only improve the utilization of spectrum resources, but also enable flexible networking and increase the coverage of wireless communication signals;

[0046] 2. The secure communication solution proposed by the present invention can ensure the physical layer security of the near user while basically not affecting the untrusted far user from receiving its own message. That is, the present invention can effectively prevent the untrusted far user from obtaining the message of the trusted near user without affecting the communication reliability of the untrusted far user.

[0047] 3. The secure communication scheme based on artificial noise and relay cooperation strategy designed by the present invention, under the premise of realizing secure communication between the ground base station and the trusted near user, hardly affects the efficient reception of the untrusted far user's own message, that is, it hardly affects the communication reliability of the untrusted far user. Under the premise of ensuring the secure communication of the trusted users of the drone NOMA network, it hardly affects the decoding of the untrusted user's own message. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] Figure 1 A system model diagram of a secure communication solution based on artificial noise in a drone NOMA network of the present invention;

[0049] Figure 2 This is a flow chart of a secure communication solution based on artificial noise in a drone NOMA network of the present invention;

[0050] Figure 3 A comparison diagram of the interruption probability of near users and far users, and the eavesdropping probability of far users between the present invention and the comparative solution;

[0051] Figure 4 This is a comparison chart of the safe and reliable equalization performance of near users and the interference reliable equalization performance of far users between the present invention and the comparative solution. DETAILED DESCRIPTION

[0052] The technical solution of the present invention is further described below in conjunction with the accompanying drawings.

[0053] In the case that the UAV cooperative NOMA network is attacked by untrusted users eavesdropping, the present invention proposes a secure communication scheme based on artificial noise in the UAV NOMA network. The secure communication scheme designed by the present invention based on artificial noise and relay cooperation strategy, while realizing secure communication between the ground base station and the trusted near user, hardly affects the untrusted far user's efficient reception of its own message, that is, it hardly affects the communication reliability of the untrusted far user.

[0054] A secure communication scheme based on artificial noise in UAV NOMA networks is applied to cooperative NOMA communication systems where UAVs are relay nodes and untrusted users exist. Figure 1As shown, the system includes a ground base station, a drone equipped with multiple antennas, a near user equipped with two antennas, and an untrusted far user equipped with a single antenna, such as Figure 2 As shown, the secure communication scheme includes the following steps:

[0055] In the first time slot, the ground base station uses NOMA technology to linearly superimpose the signal x1 sent to the near user and the signal x2 sent to the far user to obtain a mixed signal Among them, α1 and α2 represent the power allocation coefficients of the credible near user and the untrusted far user signals, respectively, and α2>α1>0, α1+α2=1; at the same time, the drone as a relay node uses antenna selection technology to select an optimal antenna to send the artificial noise signal x J For NOMA users, the remaining antennas receive signal x; at this time, the credible user sends artificial noise x J1 Interfere with untrusted users and prevent them from obtaining x J In the second time slot, the drone decodes the near user signal x1 and the artificial noise signal x generated in the first time slot. J As a bit string, perform XOR addition operation to obtain the signal Then use the NOMA mechanism to Linearly superimpose the signal x2 of the distant user to obtain the signal And use the antenna selection technology again to select the best antenna to x r The signal is sent to the NOMA user, and then the trusted near user and the untrusted far user calculate the signal-to-interference-noise ratio or signal-to-noise ratio of their respective signals based on the received signal, and further calculate the corresponding interruption probability and eavesdropping probability. From a practical point of view, the present invention is based on the worst case scenario, assuming that the untrusted far user has a strong eavesdropping ability as an eavesdropper, that is, the untrusted far user receives x in the second time slot. r Then you can ignore the interference of x2 and directly monitor the signal you want to eavesdrop on. decoding.

[0056] The signal-to-interference-to-noise ratios of the decoded signals x2 and x1 of the drone relay node in the first time slot are:

[0057]

[0058] Among them, Ψ is the set of N antennas of the drone, is the set of N-1 antennas remaining after antenna selection, Indicates the source to The column vector composed of the instantaneous channel state information of the antennas in, is the precoding vector based on the null space technique, is the vector transpose symbol; P S is the source signal transmission power, is the noise power at any receiving antenna of the drone, γ rr is the residual self-interference of the drone node; NOMA users need to obtain the artificial noise signal x sent by the drone relay node when decoding their own signals J , the near user and the untrusted far user decode the artificial noise signal x J The signal-to-interference-noise ratios are:

[0059]

[0060] in, and are the instantaneous channel state information from the i-th antenna of the drone to the near user and the far user, respectively. is the instantaneous channel state information from near users to far users, is the residual self-interference signal near the user; P r1 is the power of the artificial noise signal sent by the drone in the first time slot, and are the noise powers of near users and far users respectively.

[0061] The second time slot near user decoded signal x2 and The signal-to-interference-noise ratio and signal-to-noise ratio are:

[0062]

[0063] in, is the instantaneous channel state information from the kth antenna of the drone to the near user in the second time slot, P r2 is the signal transmission power of the drone in the second time slot; the signal-to-interference-noise ratio of the far user decoding signal x2 is:

[0064]

[0065] in, is the instantaneous channel state information from the kth antenna of the drone to the untrusted remote user in the second time slot; the untrusted remote user, as an eavesdropper, has strong eavesdropping ability, so its decoding The signal-to-noise ratio is:

[0066]

[0067] The near user interruption probability is:

[0068]

[0069] The probability that the near user is eavesdropped is:

[0070]

[0071] in, and are the thresholds for decoding signals x1 and x2, r1 and r2 are the information rate thresholds for signals x1 and x2, is the threshold value for an untrusted user to eavesdrop on the nearby user signal x1, r e is the eavesdropping information rate threshold; the interruption probability of untrusted remote users is:

[0072]

[0073] The signal-to-noise ratio calculation process of the drone relay node decoding signals x1 and x2 in the first time slot, and the NOMA user decoding artificial noise signal x J The signal-to-noise ratio calculation process is as follows: First, the drone as a relay node selects an antenna from the N antenna set Ψ to send an artificial noise signal x J , the antenna selection rule is The remaining N-1 antennas form a set of Used to receive the signal sent by the source, and the user sends an artificial noise signal x at the same time J1 Interference is performed on untrusted distant users; thus the signal received by the drone is:

[0074]

[0075] in, represents the column vector composed of additive Gaussian white noise of each receiving signal antenna at the drone relay node, is the precoding vector based on the null space technology, which is used to eliminate the artificial noise signal x at the drone relay node J1 ,satisfy Thus, the signal-to-interference-noise ratio is calculated and Because the signal-to-interference-to-noise ratio and Maximization is equivalent to Maximization of The optimization problem under The received signals of near user and far user are and in, and denote the additive Gaussian white noise at the trusted near user and the untrusted far user respectively; because the secure communication scheme is based on the relay cooperation strategy and XOR operation, the final NOMA user needs to use the artificial noise signal x J Obtain the source message, so you need to calculate x J According to the signal received by the NOMA user, the decoded x J The signal-to-interference-noise ratio is and

[0076] The signal-to-interference-to-noise ratio calculation process of the received signal in the second time slot is as follows: The drone as a relay node calculates the instantaneous channel state information from each antenna to the nearest user in the second time slot. Select an antenna to send the superimposed signal For NOMA users, the antenna selection rule is The received signals for the near user and the far user are and Combined with the NOMA transmission mechanism, the near user decoding signal x2 and The signal-to-interference-noise ratio and signal-to-noise ratio are and The signal-to-interference-to-noise ratio of the far user decoding x2 is As a strong eavesdropper, the remote user needs to decode the signal Combined with the x obtained in the first time slot J To successfully eavesdrop on x1, it is easy to get remote user decoding The signal-to-noise ratio is

[0077] The calculation process of the interruption probability of two NOMA users is as follows: Since the secure communication scheme combines artificial noise and relay cooperation strategy, it is too complicated to directly calculate the interruption probability of NOMA users, so the probability of NOMA users successfully obtaining their own messages is calculated first; According to the NOMA transmission mechanism and relay cooperation strategy, the near user and the far user decode their respective messages, and the data transmission of the first time slot ends. To successfully decode signals x2 and x1, the drone only needs and Near users also need to decode x J ,Right now In the second time slot, the near user signal x1 and the artificial noise signal x J After XOR addition, the nearest user needs to decode signal x1 and needs to decode x2 and Then the signal x obtained from the first time slot J , we can get x1, so Based on this analysis, the probability that the nearest user successfully decodes x1 is Thus, the interruption probability P can be obtained out1 ; For the far user to successfully obtain x2, the signal-to-interference-to-noise ratio of the first time slot also needs to meet the condition and In the second time slot, according to the NOMA mechanism, the far user successfully decodes the signal x2, only if the condition Therefore, the probability that the remote user successfully decodes x2 is From this, we can directly get the interruption probability of the remote user as P out2; For an untrusted remote user to successfully eavesdrop on x1, the drone relay node must also successfully decode the source message, and the remote user must also obtain the signal x at the same time J and Right now Therefore, the probability that an untrusted remote user successfully eavesdrops on the message x1 of the nearby user is:

[0078]

[0079] Example

[0080] The following is a simulation of the interruption probability of trusted near users and untrusted far users, as well as the eavesdropping probability of trusted near users being eavesdropped on by Matlab on a computer. In the simulation experiment, after normalization, the base station position is (0,-1,0), the drone position is (0,0,1), the near user position is (0,2,0), and the far user position is (1,4,0). The channel gain obeys the Nakagami distribution, the shape parameter is 2, and the channel fading coefficient is 3. The signal transmission power of each node is equal, which is P, and the noise power of each node is equal, that is, The transmission signal-to-noise ratio is The power allocation coefficients of NOMA users are α1=0.1, α2=0.9, and the residual self-interference λ rr =0.02λ sr ,λ 11 =0.02λ r1 , γ I =1. Threshold value γ1 = 7, γ2 = 3. The threshold value for an untrusted remote user to eavesdrop on a nearby user is γ e =3. In the following, the security-reliability tradeoff (SRT) is used to characterize the security of near users. Note that the interruption probability of untrusted far users obtaining their own messages and the eavesdropping probability of obtaining trusted users' messages cannot be reduced at the same time, that is, if one of the performance indicators is improved, the other performance indicator will deteriorate. The relationship between the two is called interference-reliability tradeoff (IRT).

[0081] Figure 3 The figure is a comparison chart of the interruption probability and eavesdropping probability curves of the present invention, the scheme without artificial noise and the traditional artificial noise scheme. Figure 3It can be seen that the interruption probability of the near user of the present invention is slightly worse than that of the scheme without artificial noise, but is much better than the interruption performance of the traditional artificial noise scheme. At the same time, the eavesdropping probability of the far user of the present invention is smaller than that of the traditional artificial noise scheme, and is much smaller than that of the scheme without artificial noise. The interruption probability of the far user of the present invention and the scheme without artificial noise is basically the same, but is much better than the traditional artificial noise scheme. From the above description, it can be seen that the present invention takes into account the security of the near user and the reliability of the far user, while the traditional artificial noise scheme and the scheme without artificial noise can only make one of the performance indicators of the security of the near user or the reliability of the far user basically the same as the present invention, but the other performance indicator is far worse than the present invention.

[0082] Figure 4 The following is a curve comparison of the safe and reliable equalization performance and interference reliable equalization performance of the present invention, the solution without artificial noise and the traditional artificial noise solution. Figure 4 It can be seen that the safety and reliable equalization performance of near users and the interference reliable equalization performance of far users of the present invention are better than the corresponding performances of the traditional artificial noise scheme and the scheme without artificial noise, and the traditional artificial noise scheme and the scheme without artificial noise can only make one of the safety and reliable equalization performance and the interference reliable equalization performance better, and the other performance indicator deteriorates sharply.

Claims

1. A secure communication method based on artificial noise in UAV NOMA network, It is characterized in that A collaborative NOMA communication system is applied to a drone as a relay node and there are untrusted users. The system includes a ground base station, a drone equipped with multiple antennas, a trusted near user equipped with two antennas, and an untrusted far user equipped with a single antenna. The secure communication method includes the following steps: Step 1: In the first time slot, the base station as the source uses the NOMA mechanism to superimpose and send the signal. The drone relay node selects an antenna to send an artificial noise signal, and the reliable nearby user also sends another artificial noise signal at the same time. Step 2: The drone and NOMA user calculate the signal-to-interference-noise ratio based on the received signal; Step 3: If the drone relay node fails to decode the source signal, it is directly determined that the communication is interrupted and jumps to step 5; if the drone relay node successfully decodes the source signal, in the second time slot, the drone relay node XORs the artificial noise of the first time slot and the decoded near-user signal, and then uses the NOMA mechanism to superimpose the signal and send it to the NOMA user; Step 4: The NOMA user calculates the signal-to-interference-plus-noise ratio and the signal-to-noise ratio based on the received signal; Step 5: The trusted near user and the untrusted far user calculate the corresponding interruption probability and eavesdropping probability respectively according to the obtained signal-to-interference-plus-noise ratio and signal-to-noise ratio.

2. According to claim 1, a secure communication method based on artificial noise in a drone NOMA network, It is characterized in that Step 1 is as follows: the base station as the signal source adopts the NOMA mechanism to transmit the signal x 1 and x 2 Linear superposition Then x is sent, and the drone relay node selects an antenna to send the artificial noise signal x J , it is believed that the nearby user also sends another artificial noise signal x J1 Interference with untrusted distant users.

3. According to claim 1, a secure communication method based on artificial noise in a drone NOMA network, It is characterized in that Step 2 is as follows: In the first time slot, the drone relay node decodes the signal x 2 and x 1 The signal-to-interference-noise ratios are: Among them, Ψ is the set of N antennas of the drone, is the set of N-1 antennas remaining after antenna selection, Indicates the source to The column vector composed of the instantaneous channel state information of the antennas in, is the precoding vector based on the null space technique, is the vector transpose symbol; P S is the source signal transmission power, is the noise power at any receiving antenna of the drone, γ rr is the residual self-interference of the drone node; NOMA users need to obtain the artificial noise signal x sent by the drone relay node when decoding their own signals J , the credible near user and the untrusted far user decode the artificial noise signal x J The signal-to-interference-noise ratios are: in, and are the instantaneous channel state information from the i-th antenna of the drone to the near user and the far user, respectively. is the instantaneous channel state information from near users to far users, is the residual self-interference signal near the user; P r1 is the power of the artificial noise signal sent by the drone in the first time slot, and are the noise powers of near users and far users respectively.

4. According to claim 3, a secure communication method based on artificial noise in a drone NOMA network, It is characterized in that The first time slot drone relay node decodes the signal x 1 and x 2 The signal-to-interference-noise ratio calculation process and the NOMA user decoding artificial noise signal x J The signal-to-interference-noise ratio calculation process is: First, the drone as a relay node selects an antenna from the N antenna set Ψ to send an artificial noise signal x J , the antenna selection rule is: in, represents the channel state information from the jth antenna of the drone to the nearest user, and the set of the remaining N-1 antennas is Used to receive the signal sent by the source, and the artificial noise signal x can be sent by the nearby user at the same time J1 Interference is performed on untrusted distant users; thus the signal received by the drone is: in, represents the column vector composed of additive Gaussian white noise of each receiving signal antenna at the drone relay node, is the precoding vector based on the null space technology, which is used to eliminate the artificial noise signal x at the drone relay node J1 ,satisfy Thus, the signal-to-interference-noise ratio is calculated and Because the signal-to-interference-noise ratio and Maximization is equivalent to Maximization of The following optimization problem: The received signals of the trusted near user and the untrusted far user are: in, and denote the additive Gaussian white noise at the trusted near user and the untrusted far user respectively; because the secure communication scheme is based on the relay cooperation strategy and XOR operation, the final NOMA user needs to use the artificial noise signal x J Obtain the source message, so you need to calculate x J According to the signal received by the NOMA user, the decoded x J The signal-to-interference-noise ratio is and 5. According to claim 1, a secure communication method based on artificial noise in a drone NOMA network, It is characterized in that Step 3 is as follows: if the drone relay node fails to decode the source signal, the communication is directly determined to be interrupted and the process goes to step 5; if the drone relay node succeeds in decoding the source signal, the second time slot will be x 1 and x J XOR addition Then adopt NOMA mechanism and x 2 Linear superposition Finally, x r Sent to NOMA users.

6. A secure communication method based on artificial noise in a drone NOMA network according to claim 5, It is characterized in that The second time slot, x 2 and The signal-to-interference-noise ratio and signal-to-noise ratio are: in, is the instantaneous channel state information from the kth antenna of the drone to the near user in the second time slot, P r2 is the signal transmission power of the drone in the second time slot; the decoded signal x of the untrusted remote user 2 The signal-to-interference-noise ratio is: in, is the instantaneous channel state information from the kth antenna of the drone to the untrusted remote user in the second time slot; the untrusted remote user, as an eavesdropper, has strong eavesdropping ability, so its decoding The signal-to-noise ratio is:

7. A secure communication method based on artificial noise in a drone NOMA network according to claim 1, It is characterized in that Step 4 is as follows: the credible user receives the signal Calculate the signal-to-interference-noise ratio Untrusted remote users receive signals based on Calculated signal-to-noise ratio Untrusted remote users need to eavesdrop 1 , the signal-to-noise ratio needs to be calculated Combined with the signal-to-interference-noise ratio Decode x 1 .

8. A secure communication method based on artificial noise in a drone NOMA network according to claim 1, It is characterized in that Step 5 is as follows: The probability of reliable user interruption is: The probability that a trusted user is eavesdropped is: in, and The decoded signals x are 1 and x 2 The threshold value, r 1 and r 2 The signal x 1 and x 2 The information rate threshold is is an untrusted user eavesdropping on the nearby user's signal x 1 The threshold value, r e is the eavesdropping information rate threshold; the interruption probability of untrusted remote users is:

9. A computer device comprising a memory, a processor and a computer program stored in the memory, It is characterized in that The processor executes the computer program to implement the steps of the method of claim 1.

10. A computer-readable storage medium having a computer program / instructions stored thereon, It is characterized in that When the computer program / instructions are executed by a processor, the steps of the method according to claim 1 are implemented.

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