Physical layer secure antenna selection method based on MIMO-NOMA system

Abstract

The invention provides a physical layer secure antenna selection method based on an MIMO-NOMA system, and relates to the technical field of information security. According to the method, a downlink MIMO-NOMA communication system is established, two kinds of safety antenna selection strategies are designed, the received signal power of legal users is maximized, and the signal power of eavesdropping user receivers is minimized; and the unmanned aerial vehicle transmits the superposed signal, the user receives the signal and decodes the received signal, then the traversal rate of the legal user is solved, and the probability of successfully decoding the transmission information is reduced for the potential eavesdropping user. According to the method, the antenna selection strategy is optimized, the received signal power between the source node and the legal user is maximized, the probability that the eavesdropping user successfully decodes the legal signal is reduced, and the secrecy performance of the system can be improved while the service quality of the legal user is ensured.

Description

Technical Field

[0001] The present invention relates to the field of information security technology, and in particular to a physical layer security antenna selection method based on a MIMO-NOMA system. Background Art

[0002] The development of 6G networks fills the gap between 5G and market demand. 6G networks have significantly improved data transmission speed and latency reduction. Their high reliability and wide connectivity further broaden the application scope of wireless networks. However, in the face of emergencies or unconventional temporary scenarios, such as network reconstruction after major natural disasters, temporary communication deployment in remote areas, or wireless resource allocation at major holiday gatherings, relying solely on ground wireless communication facilities may not achieve ideal communication effects. In order to improve the communication quality in these scenarios, drones can be deployed to enhance communication coverage and stability. For example, in high-density communication user scenarios, drones can be used as temporary drones or repeaters to enhance wireless communication, thereby increasing user capacity. In addition, drones can also be used as terminal users with high mobility to collect and transmit data in applications such as environmental monitoring. In order to meet the growing needs of ground users, downlink multiple access (MA) technology is essential to achieve data transmission rate requirements, low latency and connectivity without increasing resources. Non-orthogonal multiple access technology (NOMA) allows many users to share the same time or frequency resources and distinguish users in the power domain or code domain, which can effectively improve the spectrum efficiency and user fairness of the next generation wireless communication network. NOMA works by serving multiple users simultaneously in the power domain, transmitting superimposed messages to users at different power levels via unmanned aerial vehicles (UAVs), and using successive interference cancellation (SIC) technology to decode the messages at the receiving end.

[0003] With the rapid development of wireless network technology, information security issues have become increasingly prominent. The broadcast nature of wireless transmission makes information vulnerable to eavesdropping and interference, which poses a challenge to protecting the confidentiality and integrity of communications. Physical layer security (PLS) technology has emerged as the times require. It enhances the security of communications by utilizing the inherent characteristics of wireless channels. Compared with traditional upper-layer encryption protocols, PLS provides a more basic security guarantee. The core of physical layer security technology is to utilize the characteristics of wireless channels, such as multipath propagation, time-varying and spatial selectivity of channels, to achieve secure communications. This technology does not need to rely on complex key management and distribution, but instead ensures the security of information through physical means. For example, through beamforming technology, the energy of wireless signals can be concentrated in the receiving area of ​​legitimate users, thereby reducing the possibility of signals being intercepted by illegal users. In order to further improve the security of wireless communication systems, researchers are also exploring how to better integrate physical layer security technology with existing communication systems. The paper "Secrecy Sum Rate Maximization in Non-orthogonal Multiple Access" takes into account the physical layer security of large-scale NOMA networks, studies the secrecy rate of single-input single-output (SISO) NOMA systems, and derives a closed-form optimal solution for power allocation based on the user's quality of service (QoS) requirements. The paper "Physical layer security for 5G non-orthogonal multipleaccess in large-scale networks" uses a random geometry method to accurately locate users and potential eavesdroppers in MISO communication systems. This method uses the geometric properties of random distributions to simulate the random positions of users and eavesdroppers in space. In order to enhance the security of information, they set up a protection zone around the information source, and derived the exact formula and asymptotic approximation formula for the secrecy outage probability (SOP) to evaluate the secrecy performance of this system.

[0004] It can be seen from the above results that most scholars currently consider SISO or MISO systems with Rayleigh fading channels, and all of them are realized under ideal conditions that strong users can always successfully decode the information of weak users and eavesdropping users have strong detection capabilities and can distinguish multi-user data streams generated by superimposed transmission signals without interference. However, the application of MIMO and the consideration of some fading channels have not yet been involved.

[0005] In summary, although non-orthogonal multiple access (NOMA) networks perform well in improving spectrum efficiency and user fairness, they have significant defects in physical layer security (PLS). Especially in the multiple-input multiple-output (MIMO) environment, the confidentiality performance of NOMA networks is often unsatisfactory when facing the threat of passive eavesdropping users. Most people only consider that the complete channel state information (CSI) is known, but in practical applications, obtaining and maintaining CSI may be very complex and resource-intensive. Secondly, the simplified processing of the eavesdropping user model may not fully capture its behavior pattern in complex attack scenarios, resulting in an incomplete threat assessment of system security. In addition, studies often analyze based on static network topology and limited user scale, ignoring the potential impact of user mobility and network dynamics on system security. In terms of power allocation strategy, existing methods may have challenges in computational complexity and real-time performance, and are difficult to adapt to the needs of practical applications. At the same time, the flexibility of user pairing strategy and the optimization of system capacity are also issues that need to be addressed in future research. In terms of the comprehensive trade-off of performance indicators, existing studies often focus too much on security and ignore other key performance indicators such as throughput, latency and energy efficiency. Actual hardware limitations and the sophisticated attack strategies that an eavesdropping user might employ are also not fully considered. Summary of the invention

[0006] The technical problem to be solved by the present invention is to address the deficiencies of the above-mentioned prior art and provide a physical layer security antenna selection method based on the MIMO-NOMA system. By optimizing the antenna selection strategy, the received signal power between the source node and the legitimate user is maximized, while reducing the probability of eavesdropping users successfully decoding the legitimate signal. This can improve the confidentiality performance of the system while ensuring the service quality of legitimate users.

[0007] In order to solve the above technical problems, the technical solution adopted by the present invention is:

[0008] A physical layer security antenna selection method based on a MIMO-NOMA system comprises the following steps:

[0009] Step 1: Establish a downlink MIMO-NOMA communication system, which consists of an L U UAV with root antenna, legal user is equipped with L N The number of users near the root antenna U N , equipped with L F Remote user U F and equipment Eavesdropping user E with root antenna v ;

[0010] Step 2: Design a secure antenna selection strategy to maximize the received signal power of legitimate users and minimize the signal power of eavesdropping users; including two TAS selection strategies TAS-max-U F and TAS-max-U N ,Both strategies need to operate on the cumulative distribution functions of the corresponding legitimate users;

[0011] Step 3: The drone transmits the superimposed signal and the user receives the signal; in the MIMO-NOMA system, the drone sends the superimposed signal to the legitimate user, and the user captures these signals using their respective receiving antennas and uses maximum ratio combining technology to enhance the signal reception quality;

[0012] Step 4: User decoding of received signals; After the legitimate user terminal receives the superimposed signal, the near user first decodes the symbol and power level of the far user through the serial interference cancellation technology in the NOMA technology, eliminates the interference of the far user, and then decodes its own signal; the far user decodes the signal by treating the signal of the near user as noise;

[0013] Step 5: Calculate the ergodic rate of legal users. Regardless of the antenna selection strategy, the ergodic rate of near users is calculated using the Gauss-Lagrange method, and the ergodic rate of far users is calculated using the Chebyshev method.

[0014] Step 6: For potential eavesdropping users, reduce their probability of successfully decoding the transmitted information; no matter which antenna strategy is selected, the calculation method of the ergodic rate of the eavesdropping user's received signal is the same as that of the legitimate user.

[0015] Furthermore, in step 1, all nodes in the downlink MIMO-NOMA communication system are equipped with multiple antennas, where the large-scale fading in the channel is modeled as in represents the fading gain of link l between antenna i and antenna j, β l represents the large-scale fading coefficient; represents the channel small-scale fading coefficient, which is modeled as an independent Nakagami-m distribution, that is, where i∈{1,…,L U},j∈{1,…,L l},l∈{U N ,U F ,E v}, L U Indicates the number of drone antennas; L l Represents the nearest user U N Remote user U F Or eavesdrop on user E v The number of antennas, i.e. L N, L F or Based on this, the probability density function and cumulative distribution function of each user are obtained, and the formula is as follows:

[0016] The probability density function is:

[0017]

[0018] The cumulative distribution function is:

[0019]

[0020] Among them, Γ(m l ) represents the gamma function, m l represents the shape factor, Ω l represents the mean value of the power gain of small-scale fading, which is related to link l, l∈{U N ,U F ,E v};Ω i represents the mean power gain of multiple antennas of the UAV, Represents Ω i m l Power.

[0021] Furthermore, in step 2, TAS-max-U F In this mode, the received signal power of the legitimate users among the remote users is maximized, so the transmitting end L U Among the antennas, select the one with the best channel from the drone to the distant user, that is:

[0022]

[0023] Among them, i * Indicates the best antenna selected, represents the power of the channel from antenna i in the drone to the far user, L l ≤i≤L U Indicates the range of antenna numbers to be selected. At this time, L l The value is L F ;

[0024] TAS-max-U N In this mode, the received signal power of the nearest user among the legitimate users is maximized, so the transmitting end L U Among the root antennas, select the one with the best channel from the drone to the near user, that is:

[0025]

[0026] Among them, i * Indicates the best antenna selected, represents the power of the channel from antenna i to the near user in the drone, L l ≤i≤L U Indicates the range of antenna numbers to be selected. At this time, L l The value is L N .

[0027] Furthermore, in step 3, the user is allowed to achieve efficient data transmission on the same spectrum resources, and the maximum ratio combining technology improves the signal-to-noise ratio by combining signal copies received by multiple antennas; in the maximum ratio combining technology, the signal on each receiving antenna is multiplied by a weight, which corresponds to the complex conjugate of the signal on the transmitting antenna and is normalized according to the amplitude of the signal.

[0028] Furthermore, in step 4, the signal to interference noise ratio of the near user decoding the far user is:

[0029]

[0030] Among them, a F represents the power allocation coefficient of the distant user, P represents the total transmission power of the signal, represents the power of the channel from antenna i in the UAV to the near user;

[0031] The signal-to-interference-to-noise ratio of the near user decoding its own signal is:

[0032]

[0033] Among them, a N represents the power allocation coefficient near the user;

[0034] The signal-to-interference-to-noise ratio of the distant user decoding its own signal is:

[0035]

[0036] in, represents the power of the channel from antenna i in the UAV to the far user;

[0037] The cumulative distribution function corresponding to legitimate users is as follows:

[0038]

[0039] This formula shows that by finding or The cumulative probability of being less than or equal to a certain threshold x;

[0040] represents the cumulative distribution function of the near user decoding its own signal, that is, The cumulative probability of

[0041] represents the cumulative distribution function of the distant user decoding its own signal, that is, The cumulative probability of .

[0042] Furthermore, in step 5, the calculation formula of the traversal rate of the near user is:

[0043]

[0044] The calculation formula for the traversal rate of a remote user is:

[0045]

[0046] Among them, R N represents the transmission rate of the nearest user, R F Indicates the transmission rate of the far user.

[0047] Further, in step 6, in TAS-max-U N In this mode, the signal-to-interference-to-noise ratio of the eavesdropping user is:

[0048]

[0049] in, represents the power of the channel from antenna i in the drone to the eavesdropping user;

[0050] TAS-max-U N In this mode, the cumulative distribution function of the eavesdropping user is:

[0051]

[0052] This formula describes the probability that the strongest eavesdropping user among all eavesdropping users can decode the signal of the nearest user, φ E represents the set of all eavesdropping users, Indicates TAS-max-U N In the mode, select the maximum value of the signal-to-interference-noise ratio of the eavesdropping user from the set of all eavesdropping users;

[0053] TAS-max-U N In this mode, the calculation formula for the traversal rate of the eavesdropping user is:

[0054]

[0055] in, Indicates TAS-max-U N The eavesdropping user transmission rate in mode;

[0056] TAS-max-U F In this mode, the signal-to-interference-to-noise ratio of the eavesdropping user is:

[0057]

[0058] TAS-max-U F In this mode, the cumulative distribution function of the eavesdropping user is:

[0059]

[0060] This formula describes the probability that the strongest eavesdropping user among all eavesdropping users can decode the distant user's signal. Indicates TAS-max-U F In the mode, select the maximum value of the signal-to-interference-noise ratio of the eavesdropping user from the set of all eavesdropping users;

[0061] TAS-max-U F In this mode, the calculation formula for the traversal rate of the eavesdropping user is:

[0062]

[0063] in, Indicates TAS-max-U F The eavesdropping user transmission rate in mode.

[0064] The beneficial effects of adopting the above technical solutions are: the physical layer security antenna selection method based on the MIMO-NOMA system provided by the present invention effectively improves the physical layer security of the MIMO-NOMA network by proposing two antenna selection-based solutions, achieves higher power efficiency with lower implementation complexity, and optimizes the channel conditions of near users and far users by antenna selection. At the same time, the confidentiality performance of the system is enhanced by reducing the probability of successful decoding of eavesdropping users. The simulation results verify the performance analysis of the algorithm under the Nakagami-m channel with multiple antenna configurations and high signal-to-noise ratio conditions. In addition, the algorithm has strong flexibility and scalability, is suitable for multi-user scenarios, and can still maintain good security in large-scale networks. Even when the source node cannot obtain the channel state information of the eavesdropping user, the algorithm still exhibits robust confidentiality performance and is suitable for future wireless communication systems such as 5G and the Internet of Things. BRIEF DESCRIPTION OF THE DRAWINGS

[0065] Figure 1 A flow chart of a physical layer security antenna selection method based on a MIMO-NOMA system provided in an embodiment of the present invention;

[0066] Figure 2 A communication system model diagram of a downlink MIMO-NOMA provided in an embodiment of the present invention;

[0067] Figure 3 TAS-max-U provided in the embodiment of the present invention NThe following is the traversal rate graph of legitimate users and eavesdropping users;

[0068] Figure 4 TAS-max-U provided in the embodiment of the present invention F Below is the traversal rate graph of legitimate users and eavesdropping users.

[0069] Figure 2 Among them, 1. secure communication link; 2. non-secure communication link. DETAILED DESCRIPTION

[0070] The specific implementation of the present invention is further described in detail below in conjunction with the accompanying drawings and examples. The following examples are used to illustrate the present invention, but are not intended to limit the scope of the present invention.

[0071] This embodiment proposes a physical layer security antenna selection method based on the MIMO-NOMA system, and proposes two new antenna selection protocols, which enhance the security of the network by selecting the best transmitting antenna, taking into account the interference that the eavesdropping user may suffer during the decoding process, and providing a more realistic security analysis. In addition, the impact of system parameters such as the average transmission signal-to-noise ratio, the number of antennas, the power allocation coefficient, and the fading parameters on the confidentiality performance is analyzed, which helps to deeply understand the role of different parameters on the security of the system. Finally, the analysis and solution of this embodiment take into account the actual wireless communication environment, including user distribution, antenna configuration, and channel conditions, making the research results more practical, especially in the application scenarios of high-speed network communication and large-scale user access. These contributions provide new perspectives and solutions in the field of physical layer security of MIMO-NOMA networks, especially in the aspects of transmission antenna selection and power allocation strategy, providing innovative methods for improving system security.

[0072] like Figure 1 As shown, the method of this embodiment is specifically described as follows.

[0073] Step 1: Establish a downlink MIMO-NOMA communication system, such as Figure 2 As shown, the system includes an L U The legal user of a drone with an antenna is equipped with L N The number of users near the root antenna U N , equipped with L F Remote user U F and equipment Eavesdropping user E with root antenna v , where the communication link between the drone and the near user and the far user is the secure communication link 1, and the communication link between the drone and the eavesdropping user is the insecure communication link 2. All nodes are equipped with multiple antennas, where the large-scale fading in the channel is modeled as in represents the fading gain of link l between antenna i and antenna j, β l represents the large-scale fading coefficient; represents the channel small-scale fading coefficient, which is modeled as an independent Nakagami-m distribution, that is, where i∈{1,…,L U},j∈{1,…,L l},l∈{U N ,U F ,E v}, L U Indicates the number of drone antennas; L l Represents the nearest user U N Remote user U F Or eavesdrop on user E v The number of antennas, i.e. L N , L F or Based on this, the probability density function and cumulative distribution function of each user are obtained, and the formula is as follows:

[0074] The probability density function is:

[0075]

[0076] The cumulative distribution function is:

[0077]

[0078] Among them, Γ(m l ) represents the gamma function, m l represents the shape factor, Ω l represents the mean value of the power gain of small-scale fading, which is related to link l, l∈{U N ,U F ,E v};Ω i represents the mean power gain of multiple antennas of the UAV, Represents Ω i m l Power.

[0079] From step 1, it can be concluded that the fading characteristics of the channel (such as Nakagami-m distribution) are modeled by fading parameters. These fading parameters will affect the channel quality, and further affect the strength of the received signal and the decoding performance.

[0080] Step 2: Design a secure antenna selection strategy to maximize the received signal power of legitimate users and minimize the signal power of eavesdropping users. It includes two TAS selection strategies: TAS-max-U N and TAS-max-U F.

[0081] TAS-max-U F In this mode, the received signal power of the legitimate users among the remote users is maximized, so the transmitting end L U The antenna with the best channel from the drone to the remote user is selected among the antennas. where i * Indicates the best antenna selected, represents the power of the channel from antenna i in the drone to the far user, L l ≤i≤L U Indicates the range of antenna numbers to be selected. At this time, L l The value is L F .

[0082] TAS-max-U N In this mode, the received signal power of the legitimate users among the remote users is maximized, so the transmitting end L U The antenna with the best channel from the drone to the remote user is selected among the antennas. where i * Indicates the best antenna selected, represents the power of the channel from antenna i to the near user in the drone, L l ≤i≤L U Indicates the range of antenna numbers to be selected. At this time, L l The value is L N .

[0083] Regardless of the antenna selection strategy, the cumulative distribution function of the corresponding legitimate users needs to be operated.

[0084] Step 3: The drone transmits the superimposed signal and the user receives the signal. In MIMO-NOMA, the drone sends superimposed signals to legitimate users, who capture these signals using their respective receiving antennas and use maximum ratio combining (MRC) technology to enhance the signal reception quality. This process allows users to achieve efficient data transmission on the same spectrum resources, while MRC technology improves the signal-to-noise ratio by combining the signal replicas received by multiple antennas, thereby improving the signal decoding performance. In MIMO systems, MRC technology uses signal replicas on multiple receiving antennas to improve the signal-to-noise ratio (SNR) of the received signal. In MRC, the signal on each receiving antenna is multiplied by a weight that is the complex conjugate of the signal on the corresponding transmitting antenna and is normalized by the amplitude of the signal.

[0085] From steps 2 and 3, it can be concluded that the number of antennas has a direct impact on the quality of signal transmission and reception. By selecting appropriate antennas, the system can improve the signal reception quality of legitimate users and reduce the signal decoding ability of eavesdropping users.

[0086] Step 4: User decoding of received signals. After the legitimate user terminal receives the superimposed signal, the near user first decodes the symbol and power level of the far user through the serial interference cancellation (SIC) technology in the NOMA technology, eliminates the interference of the far user, and then decodes its own signal; the far user decodes the signal by treating the near user's signal as noise.

[0087] Among them, the signal to interference and noise ratio (SINR) of the near user decoding the far user is:

[0088]

[0089] Among them, a F represents the power allocation coefficient of the distant user, P represents the total transmission power of the signal, It represents the power of the channel from antenna i to the near user in the UAV.

[0090] The signal-to-interference-to-noise ratio of the near user decoding its own signal is:

[0091]

[0092] Among them, a N represents the power allocation coefficient of the near user, P represents the total transmission power of the signal, It represents the power of the channel from antenna i to the near user in the UAV.

[0093] The signal-to-interference-to-noise ratio of the distant user decoding its own signal is:

[0094]

[0095] Among them, a F represents the power allocation coefficient of the distant user, P represents the total transmission power of the signal, It represents the power of the channel from antenna i in the UAV to the far user.

[0096] The cumulative distribution function corresponding to legitimate users is as follows:

[0097]

[0098] This formula shows that by finding or The cumulative probability of being less than or equal to a certain threshold x.

[0099] Step 5: Calculate the ergodic rate of the legitimate user. Regardless of the antenna selection strategy, the ergodic rate of the near user is calculated using the Gaussian Lagrangian method, and the calculation formula is:

[0100]

[0101] The traversal rate of the remote user is solved by Chebyshev's method, and the calculation formula is:

[0102]

[0103] From step 4 and step 5, it can be concluded that the adjustment of the power allocation coefficient determines the signal strength of each user, thereby affecting the signal to noise ratio (SNR). Reasonable power allocation can improve the quality of the received signal of the legitimate user while reducing the probability of successful decoding of the eavesdropping user.

[0104] Step 6: For potential eavesdroppers, reduce their probability of successfully decoding the transmitted information. Regardless of the antenna strategy selected, the calculation method of the ergodic rate of the received signal of the eavesdropper is the same as that of the legitimate user.

[0105] TAS-max-U N In this mode, the signal-to-interference-to-noise ratio of the eavesdropping user is:

[0106]

[0107] Among them, a N represents the power allocation coefficient of the near user, P represents the total transmission power of the signal, It represents the power of the channel from antenna i to the near user in the UAV.

[0108] TAS-max-U N In this mode, the cumulative distribution function of the eavesdropping user is:

[0109]

[0110] This formula describes the probability that the strongest eavesdropping user among all eavesdropping users can decode the signal of the nearest user, φ E represents the set of all eavesdropping users, Indicates TAS-max-U N In this mode, the maximum value of the signal-to-interference-noise ratio of the eavesdropping user is selected from the set of all eavesdropping users.

[0111] TAS-max-U N In this mode, the calculation formula for the traversal rate of the eavesdropping user is:

[0112]

[0113] in, Indicates TAS-max-U N The eavesdropping user transmission rate in mode.

[0114] TAS-max-U F In this mode, the signal-to-interference-to-noise ratio of the eavesdropping user is:

[0115]

[0116] Among them, a F represents the power allocation coefficient of the distant user, P represents the total transmission power of the signal, It represents the power of the channel from antenna i in the UAV to the far user.

[0117] TAS-max-U F In this mode, the cumulative distribution function of the eavesdropping user is:

[0118]

[0119] This formula describes the probability that the strongest eavesdropping user among all eavesdropping users can decode the distant user's signal, φ E represents the set of all eavesdropping users, Indicates TAS-max-U F In this mode, the maximum value of the signal-to-interference-noise ratio of the eavesdropping user is selected from the set of all eavesdropping users.

[0120] TAS-max-U F In this mode, the calculation formula for the traversal rate of the eavesdropping user is:

[0121]

[0122] in, Indicates TAS-max-U F This method can effectively handle the complex channel effects caused by signal reflection and scattering, thus providing an accurate mathematical model for the performance analysis of eavesdropping users.

[0123] The method proposed in this embodiment aims to improve the physical layer security of communications in a multiple-input multiple-output (MIMO) non-orthogonal multiple access (NOMA) network, especially in the presence of passive eavesdropping users. Through the transmission antenna selection strategy and power allocation mechanism, the method aims to enhance the signal quality of legitimate users while reducing the signal quality received by eavesdropping users, thereby improving the confidentiality of the signal and the security of the system.

[0124] Simulation conditions: In the simulation, the drone is considered to have 5 antennas, the near user among the legitimate users has 2 antennas, the far user has 2 antennas, and the eavesdropping user has 3 antennas. The height of the drone is set to be constant at H = 20m, the path loss coefficient α = 2, and the distance between the near user and the drone is d N = 65m, the distance between the far user and the drone is d F =70m. In terms of power allocation coefficient, the power allocation coefficient near the user is a N=0.4, the remote user allocation coefficient is a F = 0.6. In addition, the number of simulations is set to 5000.

[0125] Simulation content: Through TAS-max-U N and TAS-max-U F Two antenna selection strategies are simulated to study the average traversal rates of near users, far users, and eavesdropping users. Comparison of simulation results with theoretical calculation results can help us understand the impact of different antenna selection modes on system performance (including system throughput and physical layer security), especially the changes in the rates of near users and far users at different transmission powers, as well as the changes in the decoding capabilities of eavesdropping users.

[0126] Figure 3 It can be seen that in TAS-max-U N In this mode, the average traversal rate of near users increases significantly when the signal-to-noise ratio increases. The simulation results are consistent with the analysis results. The rate curve of near users shows a rapid growth trend when the signal-to-noise ratio is high, which indicates that near users can achieve higher communication rates under high signal-to-noise ratio conditions. The rate of far users varies little under different signal-to-noise ratios, indicating that far users are restricted by channel conditions in this system and it is difficult to achieve significant rate improvements. The rates of the strongest eavesdropping users on near users and the strongest eavesdropping users on far users are both low and do not change much with the signal-to-noise ratio. This phenomenon shows that TAS-max-U N The mode is designed to successfully suppress the rate of eavesdropping users, making it difficult for eavesdropping users to obtain valid information under different signal-to-noise ratio conditions, thereby improving the security of the system.

[0127] Figure 4 It can be seen that in TAS-max-U F In this mode, the average traversal rate of far users improves with the increase of SNR. Compared with near users, the rate curve of far users tends to be more stable and increases linearly with SNR, which reflects the TAS-max-U F The optimization effect of the mode on the transmission path of distant users. The rate curve of near users is compared with TAS-max-U N The change is due to the inclination of system resources toward far users, which balances the rate difference between near and far users. Although this design sacrifices the rate of near users, it enables both far and near users to maintain relatively high performance under high signal-to-noise ratio through balanced allocation. The rates of the strongest eavesdropping users on near users and the strongest eavesdropping users on far users are both low and do not increase significantly with the signal-to-noise ratio, which ensures the security of the system. In particular, for the strongest eavesdropping users on far users, their rates are still well suppressed, indicating that TAS-max-U FThe mode also has the advantage of protecting the privacy of remote user transmissions.

[0128] In summary, both antenna selection modes can increase the rate of legitimate users and suppress the rate of eavesdropping users. This method helps to improve the confidentiality of the communication link and balances the rate distribution between near users and far users to a certain extent.

[0129] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the above embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope defined by the claims of the present invention.

Claims

1. A physical layer security antenna selection method based on MIMO-NOMA system, characterized by: The following steps are involved: Step 1: Establish a downlink MIMO-NOMA communication system, which consists of an L U UAV with root antenna, legal user is equipped with L N The number of users near the root antenna U N 、Equipped with L F Remote user U F and equipment Eavesdropping user E with root antenna v ; Step 2: Design a secure antenna selection strategy to maximize the received signal power of legitimate users and minimize the signal power of eavesdropping users; including two TAS selection strategies TAS-max-U F and TAS-max-U N ,Both strategies need to operate on the cumulative distribution functions of the corresponding legitimate users; Step 3: The drone transmits the superimposed signal and the user receives the signal; in the MIMO-NOMA system, the drone sends the superimposed signal to the legitimate user, and the user captures these signals using their respective receiving antennas and uses maximum ratio combining technology to enhance the signal reception quality; Step 4: The user decodes the received signal; After the legitimate user terminal receives the superimposed signal, the near user first decodes the symbol and power level of the far user through the serial interference cancellation technology in the NOMA technology, eliminates the interference of the far user, and then decodes its own signal; The distant user decodes the signal by treating the signal of the nearby user as noise; Step 5: Calculate the ergodic rate of legal users. Regardless of the antenna selection strategy, the ergodic rate of near users is calculated using the Gauss-Lagrange method, and the ergodic rate of far users is calculated using the Chebyshev method. Step 6: For potential eavesdropping users, reduce their probability of successfully decoding the transmitted information; no matter which antenna strategy is selected, the calculation method of the ergodic rate of the eavesdropping user's received signal is the same as that of the legitimate user.

2. The physical layer security antenna selection method based on the MIMO-NOMA system according to claim 1, characterized in that: In step 1, all nodes in the downlink MIMO-NOMA communication system are equipped with multiple antennas, where the large-scale fading in the channel is modeled as in represents the fading gain of link l between antenna i and antenna j, β l represents the large-scale fading coefficient; represents the channel small-scale fading coefficient, which is modeled as an independent Nakagami-m distribution, that is, where i∈{1,…,L U },j∈{1,…,L l },l∈{U N ,U F ,E v }, L U Indicates the number of drone antennas; L l Represents the nearest user U N Remote user U F Or eavesdrop on user E v The number of antennas, i.e. L N , L F or Based on this, the probability density function and cumulative distribution function of each user are obtained, and the formula is as follows: The probability density function is: The cumulative distribution function is: Among them, Γ(m l ) represents the gamma function, m l represents the shape factor, Ω l represents the mean value of the power gain of small-scale fading, which is related to link l, l∈{U N ,U F ,E v };Ω i represents the mean power gain of multiple antennas of the UAV, Represents Ω i m l Power.

3. The physical layer security antenna selection method based on the MIMO-NOMA system according to claim 2 is characterized in that: In step 2, TAS-max-U F In this mode, the received signal power of the legitimate users among the remote users is maximized, so the transmitting end L U Among the antennas, select the one with the best channel from the drone to the distant user, that is: Among them, i * Indicates the best antenna selected, represents the power of the channel from antenna i in the drone to the far user, L l ≤i≤L U Indicates the range of antenna numbers to be selected. At this time, L l The value is L F ; TAS-max-U N In this mode, the received signal power of the nearest user among the legitimate users is maximized, so the transmitting end L U Among the root antennas, select the one with the best channel from the drone to the near user, that is: Among them, i * Indicates the best antenna selected, represents the power of the channel from antenna i to the near user in the drone, L l ≤i≤L U Indicates the range of antenna numbers to be selected. At this time, L l The value is L N .

4. The physical layer security antenna selection method based on the MIMO-NOMA system according to claim 3 is characterized in that: In step 4, the signal to interference noise ratio of the near user decoding the far user is: Among them, a F represents the power allocation coefficient of the distant user, P represents the total transmission power of the signal, represents the power of the channel from antenna i in the UAV to the near user; The signal-to-interference-to-noise ratio of the near user decoding its own signal is: Among them, a N represents the power allocation coefficient near the user; The signal-to-interference-to-noise ratio of the distant user decoding its own signal is: in, represents the power of the channel from antenna i in the UAV to the far user; The cumulative distribution function corresponding to legitimate users is as follows: This formula shows that by finding or The cumulative probability of being less than or equal to a certain threshold x; represents the cumulative distribution function of the near user decoding its own signal, that is, The cumulative probability of represents the cumulative distribution function of the distant user decoding its own signal, that is, The cumulative probability of .

5. The physical layer security antenna selection method based on the MIMO-NOMA system according to claim 4 is characterized in that: In step 5, the calculation formula of the traversal rate of the near user is: The calculation formula for the traversal rate of a remote user is: Among them, R N represents the transmission rate of the nearest user, R F Indicates the transmission rate of the far user.

6. The physical layer security antenna selection method based on the MIMO-NOMA system according to claim 5, characterized in that: In step 6, in TAS-max-U N In this mode, the signal-to-interference-to-noise ratio of the eavesdropping user is: in, represents the power of the channel from antenna i in the drone to the eavesdropping user; TAS-max-U N In this mode, the cumulative distribution function of the eavesdropping user is: This formula describes the probability that the strongest eavesdropping user among all eavesdropping users can decode the signal of the nearest user, φ E represents the set of all eavesdropping users, Indicates TAS-max-U N In the mode, select the maximum value of the signal-to-interference-noise ratio of the eavesdropping user from the set of all eavesdropping users; TAS-max-U N In this mode, the calculation formula for the traversal rate of the eavesdropping user is: in, Indicates TAS-max-U N The eavesdropping user transmission rate in mode; TAS-max-U F In this mode, the signal-to-interference-to-noise ratio of the eavesdropping user is: TAS-max-U F In this mode, the cumulative distribution function of the eavesdropping user is: This formula describes the probability that the strongest eavesdropping user among all eavesdropping users can decode the distant user's signal. Indicates TAS-max-U F In the mode, select the maximum value of the signal-to-interference-noise ratio of the eavesdropping user from the set of all eavesdropping users; TAS-max-U F In this mode, the calculation formula for the traversal rate of the eavesdropping user is: in, Indicates TAS-max-U F The eavesdropping user transmission rate in mode.

7. The physical layer security antenna selection method based on the MIMO-NOMA system according to claim 1, characterized in that: In step 3, the user is allowed to achieve efficient data transmission on the same spectrum resources, and the maximum ratio combining technology improves the signal-to-noise ratio by combining signal copies received by multiple antennas; In the maximum ratio combining technique, the signal at each receive antenna is multiplied by a weight that corresponds to the complex conjugate of the signal at the transmit antenna and is normalized by the amplitude of the signal.

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