Secure ultra-reliable and low-latency communication method in noma wireless network supported by uav

Abstract

The application provides a secure ultra-reliable and low-latency communication method in a UAV-supported NOMA wireless network, comprising the following steps: S1, establishing a network model, a channel model and performance indexes of physical layer security under short block length constraints; S2, analyzing a connection outage probability COP, a secrecy outage probability SOP and a secrecy transmission capacity STC of a static unmanned aerial vehicle; S3, maximizing a secrecy rate by optimizing an eavesdropping code rate and optimizing power allocation; S4, analyzing the COP, the SOP and the STC of a dynamic unmanned aerial vehicle; S5, simulating a position of a wireless node and a message transmission process by using MATLAB, and considering network performance according to the position of the unmanned aerial vehicle and a licensed user PLR requiring privacy and low latency, so that the secure ultra-reliable and low-latency communication in the wireless network is completed. The application provides stronger received signal strength, provides an important technology for effectively covering ground wireless nodes, and has the characteristics of low latency, high reliability, high security and large-scale connection.

Description

Technical Field

[0001] This invention relates to the field of physical layer security combining unmanned aerial vehicles (UAVs) and non-orthogonal multiple access (NOMA), specifically a secure, ultra-reliable, and low-latency communication method in a NOMA wireless network supported by UAVs. Background Technology

[0002] Due to the non-negligible decoding error probability and inherent randomness of wireless channels, it is difficult to simultaneously meet the reliability and latency requirements of uRLLC. Drones or drone technology can provide stronger received signals by establishing air-to-ground line-of-sight propagation for ground users. On the other hand, besides reliability and latency, the security of information transmission in uRLLC is also extremely important due to the openness of the wireless environment. Secure wireless communication based on drones is challenging because air-to-ground line-of-sight can provide a strong channel for eavesdroppers. Based on the assumption of limited computing power, traditional encryption-based algorithms are a popular technique for providing security at higher layers of the network. However, once eavesdroppers possess powerful computing capabilities, these algorithms become ineffective. Furthermore, uRLLC cannot tolerate the significant processing delays caused by complex encryption. Against this backdrop, there is an urgent need to develop new and effective technologies for drone-based uRLLC. Summary of the Invention

[0003] To address the aforementioned issues, this invention provides a secure, ultra-reliable, and low-latency communication method for NOMA wireless networks supported by UAVs. This method can provide stronger received signal strength and is an important technology for providing effective coverage for terrestrial wireless nodes. It features low latency, high reliability, high security, and large-scale connectivity.

[0004] To achieve the above objectives, the present invention adopts the following technical solution:

[0005] The secure, ultra-reliable, and low-latency communication method in a NOMA wireless network supported by UAV includes the following steps:

[0006] S1. Establish network models, channel models, and performance indicators of physical layer security under short block length constraints;

[0007] S2. Analyze the probability of connection interruption (COP), the probability of security interruption (SOP), and the security transmission capacity (STC) of static unmanned aerial vehicles (UAVs).

[0008] S3. Maximize confidentiality by optimizing the eavesdropping code rate and power allocation;

[0009] S4. Analyze the COP, SOP, and STC of dynamic unmanned aerial vehicles (UAVs);

[0010] S5. Using MATLAB, the location of wireless nodes and the message transmission process are simulated. Based on the set network parameters, the location of the drone and the authorized users (PLRs) who require privacy and low latency are considered to ensure network performance, thereby achieving secure, ultra-reliable and low-latency communication in the wireless network.

[0011] Furthermore, in step S1, establishing the network model, channel model, and performance indicators of physical layer security under short block length constraints includes the following sub-steps:

[0012] S1.1 Consider an air-to-ground communication system implemented via a downlink wireless network from an unmanned aerial vehicle (UAV), where multiple passive eavesdroppers exist on the ground. The hovering UAV serves two types of authorized users with different performance requirements: authorized users requiring privacy and low latency (PLR), and authorized users requiring reliability and low latency (RLR). The UAV is equipped with N... t There are one antenna for each ground node. The locations of authorized users and eve are determined by a density of λ. u and λ e Two homogeneous Poisson point processes (PPPs) Φ u and Φ e Modeling;

[0013] S1.2 Considering that NOMA can share frequency resources simultaneously by using different transmit powers, the SINR of PLR users, RLR users and eavesdroppers can be obtained by using the noise power formula.

[0014] S1.3 In order to evaluate channel quality, connection interruption probability and security interruption probability are introduced;

[0015] S1.4 In order to meet the reliability requirements of RLR users while also considering the reliability and security of PLR users, the eavesdropping code rates Rt and Rs are used to maximize the confidentiality rate and solve the problem of how to maximize the network security rate.

[0016] Furthermore, in step S2, the analysis of the COP, SOP, and STC of the static UAV includes the following sub-steps:

[0017] S2.1 Based on the concept of COP, the COP of the j-th PLR user can be calculated, and the expression is:

[0018]

[0019] The total bandwidth allocated to PLR users is ξB, and the bandwidth allocated to RLR users is (1-ξ)B, where ξ∈[0,1] and B are the bandwidth allocation rate and total available bandwidth, respectively. uj Let P be the distance between the UAV and the j-th ground user. ujP is the transmit power allocated to the j-th ground user. uk It is the transmit power allocated to the k-th ground user, α l =2 is the path loss exponent in the case of Loss of Speed ​​(LoS), η l This is the channel power gain at a reference distance of one meter in this case, β. u,min The reliability threshold is the minimum SINR required for legitimate users to meet reliability constraints.

[0020] S2.2 Calculate the COP of the i-th RLR user, the expression is:

[0021]

[0022] Among them, P ui It is the transmit power allocated to the i-th ground user, g ui is the channel fading gain between the UAV and the i-th user, and v is the noise power;

[0023] S2.3. Based on the definition of SOP, the formula is derived. By using Φ e Using the probability generating function (PGFL) and Jensen's inequality, we obtain the upper bound of SOP:

[0024]

[0025]

[0026] in, β e,max Security threshold, r zone Let λ be the radius of the confidential zone. e H represents the density of eavesdroppers, and H represents the altitude of the drone.

[0027] S2.4. The condition for the j-th PLR user to achieve a positive confidentiality rate is derived as follows:

[0028]

[0029] in, For the acceptable maximum DEP of expected reliability, the expected maximum transmit power of the j-th PLR user is:

[0030]

[0031] Furthermore, in step S3, based on the analysis framework of COP, SOP, and security rate, the problem of maximizing the security rate is solved by optimizing the eavesdropping code rate and the transmission power allocation, including the following sub-steps:

[0032] S3.1 Given the UAV positioning altitude H, design the eavesdropping code rate R. t and R s The goal is to maximize the confidentiality rate while simultaneously satisfying performance levels of reliability and security. The problem of maximizing the confidentiality rate can be expressed as:

[0033]

[0034]

[0035]

[0036] 0≤ξ≤1

[0037] Consider this issue with the help of SIC. By performing confidentiality analysis, we can obtain the COP and maximum bitrate of PLR users, then calculate the total COP of the j-th PLR user, and finally solve for R. t ;

[0038] S3.2. According to step S3.1, R can be obtained. t The optimal solution is:

[0039]

[0040] in,

[0041] S3.3, By setting To obtain the optimal transmit power for the j-th PLR user, use This indicates that the total power allocated to other PLR users with stronger channel quality compared to the j-th PLR user is also set to be maximized;

[0042] S3.4, combined with the power allocation strategy given in step S3.3 to maximize the confidentiality rate of the j-th PLR user, introduces the concept of gradient descent in the algorithm. Specifically, according to the decision condition, if the gradient of the function exceeds the expected accuracy, the above two power allocations should be updated to P. uj =(1-α)P uj and P j+1 =(1-α)P j+1 Repeat this update process until the desired accuracy is achieved. Finally, the optimal power allocation for the j-th PLR user and other PLR users with better channel quality can be approximated to maximize the safe rate.

[0043] Furthermore, in step S4, the analysis of the COP, SOP, and STC of the dynamic UAV includes the following sub-steps:

[0044] S4.1 To improve the reliability performance of authorized users, suppose the i-th RLR user moves to the center of the secure zone, and the UAV flies within an inverted cone centered on the j-th PLR user with a maximum radius of D. The UAV can fly freely in any direction within the space of the inverted cone. Then, the cumulative distribution function (CDF) of the distance d between the center of the secure zone and the UAV is:

[0045]

[0046] And the probability density function (PDF) is:

[0047]

[0048] The COP for the j-th PLR user can be obtained as follows:

[0049]

[0050] By constraining θ min Maximum bitrate of dynamic drones The following is given:

[0051]

[0052] The optimal eavesdropping rate is:

[0053]

[0054] in For the expected maximum acceptable DEP, The acceptable minimum DEP for expected safety, φ min This is the minimum safety requirement;

[0055] S4.2, The condition for the j-th PLR user to obtain a positive confidentiality rate, derived from step S4.1, is as follows:

[0056]

[0057] Solve R t The problem of maximizing the security rate given a total power allocation is expressed as:

[0058]

[0059] in, For a finite block length, the global COP can be derived from this problem, and the optimal solution is:

[0060]

[0061] By combining and optimal get:

[0062]

[0063] The confidentiality rate of the j-th PLR user is the total power allocated to other PLR users at greater distances plus its own power (P). uj ) is a monotonically increasing function. Furthermore, given the constraint of power allocation to the j-th PLR user, for different total power allocations to maximize the security rate, τ can be reformulated as:

[0064]

[0065] in,

[0066] Furthermore, in step S5, the location of the wireless node and the message transmission process were simulated using MATLAB, mainly including the following sub-steps:

[0067] S5.1 Based on the set network parameters, the location of the drone and the authorized user (PLR) requiring privacy and low latency takes into account network performance, thereby completing secure, ultra-reliable and low-latency communication in the wireless network, wherein the location of the drone is (H, 0, 0), and the j-th PLR user is located at (1, 0, 0).

[0068] S5.2 Analyze the impact of different block lengths and noise power on interruption probability and decoding error probability;

[0069] S5.3 Analyze how COP and SOP change as the noise power and total power of other PLR users are allocated;

[0070] S5.4 Analyze the relationship between the security rate and transmission power and interference.

[0071] The beneficial effect of this invention is that it approximates the line-of-sight propagation gain as the Rayleigh fading gain. This approximation simplifies the analysis and provides guidance for general A2G LoS scenarios. In this way, by deriving closed-form expressions for BER-COP, BER-SOP, and confidentiality rate, an analytical framework for security, reliability, and latency performance is established for authorized users with different needs.

[0072] Based on the above framework, by analyzing the relationship between the security rate of a given PLR user and key system parameters, and with the help of NOMA, the security rate can be maximized by appropriately allocating its own transmit power and the total transmit power allocated to other licensed users with higher channel quality. This provides network designers with important insights into maximizing security rates.

[0073] By deriving a closed-form expression for the security rate on a mobile UAV, it can be found that the security rate for PLR users is a monotonically increasing function of the power allocation of the two transmissions mentioned above. Simulation results conclude that moderate interference is beneficial for achieving a positive security rate, and dynamic UAVs are an effective way to improve the security rate. Attached Figure Description

[0074] Figure 1 This is a flowchart illustrating the process of the present invention;

[0075] Figure 2 The figures show the experimental results of the network under different noise powers according to the present invention.

[0076] Figure 3 The figure shows the experimental results of the transmit power and COP allocated to PLR users according to the present invention;

[0077] Figure 4 The figure shows the experimental results of the SOP of the present invention as a function of noise power.

[0078] Figure 5 The figure shows the experimental results of the transmit power and interruption probability allocated to other PLR users according to the present invention.

[0079] Figure 6 The figure shows the experimental results of the transmission power and security level of this invention.

[0080] Figure 7 The graph shows the experimental results of the transmit power and security level allocated to other PLR users according to the present invention. Detailed Implementation

[0081] The specific technical solutions of the present invention will be described with reference to the embodiments.

[0082] In this invention, the line-of-sight propagation gain is approximated as the Rayleigh fading gain. This approximation simplifies the analysis and provides guidance for general A2G LoS scenarios. In this way, by deriving closed-form expressions for BER-COP, BER-SOP, and security rate, an analytical framework for security, reliability, and latency performance is established for licensed users with different needs. Based on this framework, by analyzing the relationship between the security rate of a given PLR user and key system parameters, and with the help of NOMA, the security rate can be maximized by appropriately allocating its own transmit power and the total transmit power allocated to other licensed users with higher channel quality. This provides network designers with important insights into maximizing the security rate. By deriving a closed-form expression for the security rate on a mobile UAV, it can be found that the security rate for a PLR user is a monotonically increasing function of the power allocation for the two transmit operations. Simulation results conclude that moderate interference is beneficial for achieving a positive security rate, and dynamic UAVs are an effective way to improve the security rate.

[0083] This invention is illustrated through the following application examples, demonstrating the steps of the secure, highly reliable, and low-latency communication method in a NOMA wireless network supported by the UAV of this invention, such as... Figure 1 As shown.

[0084] 1. Performance indicators of physical layer security

[0085] To evaluate channel quality, connection interruption probability (COP), confidentiality interruption probability (SOP), and confidential transmission capacity (STC) are introduced. Approximate expressions for COP and SOP are solved to maximize confidentiality while ensuring reliability and security.

[0086] 2. Experimental Environment Configuration

[0087] The experimental environment consisted of a 64-bit Windows 10 operating system, an Intel(R) Core(TM) i5-6500 @ 3.20Hz CPU, an NVIDIA GeForce GT 710 graphics card, 8.00GB of memory, and MATLAB version 2018b.

[0088] 3. Experimental Parameter Design

[0089] Network parameters are set as shown in the table below. Given the drone's location (H, 0, 0), consider the performance of the network enabling the drone on the j-th user with privacy and low latency requirements located at (1, 0, 0).

[0090] Simulation parameters and values

[0091]

[0092] 4. Analysis of Experimental Results

[0093] The network performance of the UAV was evaluated using the experimental parameters configured above. Figure 2 For p co The relationship between p and noise power v co The probability of a decoding error increases with increasing noise power (v), indicating that noise degrades reliability when the PLR ​​user fails to recover the message. Simultaneously, the decoding error probability also increases with increasing noise power. This is because the decoding error probability is a decreasing function of the received signal strength, which decreases with increasing noise power.

[0094] Figure 3 This indicates that for the larger transmit power allocated to other PLR users, p co It becomes larger. This phenomenon implies a decrease in reliability.

[0095] Figure 4 The probability of security breach p was summarized. soHow does p change with v? co It decreases as n decreases, while p so As n increases, this suggests that a smaller block length contributes to security, because an eavesdropper cannot successfully recover the message due to a higher probability of decoding errors.

[0096] Figure 5 The study concludes that mobile UAVs do not offer a significant improvement in security levels compared to static UAVs, but they can effectively enhance network reliability. This is because mobile UAVs are more likely to approach the ground, reducing the distance between the UAV and PLR users, thus leading to better network reliability. Similarly, mobile UAVs can worsen network security because the closer the UAV is to the eavesdropper.

[0097] Figure 6 Figure 7 Summarize P j and P j+1 How to affect the security rate of mobile UAVs? For static UAVs, how to appropriately set P? j and P j+1 To maximize the security rate, for mobile UAVs, the security rate can be increased by increasing P. j and P j+1 To maximize this. More importantly, mobile drones can achieve higher security rates than fixed drones, demonstrating that mobile drones are an effective secure communication strategy.

[0098] Compared with existing technologies, the beneficial effects of this invention are as follows: This invention approximates the line-of-sight propagation gain as the Rayleigh fading gain. This approximation simplifies the analysis and provides guidance for general A2G LoS scenarios. In this way, by deriving closed-form expressions for BER-COP, BER-SOP, and security rate, an analytical framework for security, reliability, and latency performance is established for licensed users with different needs. Based on the above framework, by analyzing the relationship between the security rate of a given PLR user and key system parameters, and with the help of NOMA, the security rate can be maximized by appropriately allocating its own transmit power and the total transmit power allocated to other licensed users with higher channel quality. This provides network designers with important insights into maximizing the security rate. By deriving a closed-form expression for the security rate on a mobile UAV, it can be found that the security rate for a PLR user is a monotonically increasing function of the power allocation of the two transmit methods mentioned above. Simulation results conclude that moderate interference is beneficial to achieving a positive security rate, and dynamic UAVs are an effective way to improve the security rate.

[0099] By addressing the security performance of uRLLC networks supporting UAV, an approximate expression for the probability of security reliability interruption in A2G wireless channels is derived using Rayleigh fading gain. Then, a lower bound for the security rate is derived in closed-form. Therefore, the system configuration is optimized to maximize the security rate while satisfying reliability and security constraints. Finally, numerical results are presented to verify the theoretical analysis, and the impact of different system parameters on secure transmission performance is shown. These results are helpful for network designers in ensuring the expected levels of reliability and security.

[0100] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the invention can be implemented in other specific forms without departing from its spirit or essential characteristics. Therefore, the embodiments should be considered in all respects as exemplary and non-limiting, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of equivalents of the claims are intended to be included within the present invention. No reference numerals in the claims should be construed as limiting the scope of the claims.

[0101] Furthermore, it should be understood that although this specification describes embodiments, not every embodiment contains only one independent technical solution. This narrative style is merely for clarity. Those skilled in the art should consider the specification as a whole, and the technical solutions in each embodiment can also be appropriately combined to form other embodiments that can be understood by those skilled in the art.

Claims

1. A secure, ultra-reliable, and low-latency communication method in a UAV-supported NOMA wireless network, characterized by: It includes the following steps: S1. Establish network models, channel models, and performance indicators of physical layer security under short block length constraints; S2. Analyze the connection interruption probability (COP), the security interruption probability (SOP), and the security transmission capacity (STC) of static UAVs. S3. Maximize confidentiality by optimizing the eavesdropping code rate and power allocation; S4. Analyze the COP, SOP, and STC of dynamic unmanned aerial vehicles (UAVs); S5. Using MATLAB, the location and message transmission process of wireless nodes are simulated. Based on the set network parameters, the location of the UAV and the authorized user PLR who requires privacy and low latency are considered to ensure network performance, thus completing secure, ultra-reliable and low-latency communication in the wireless network. In step S2, analyzing the COP, SOP, and STC of a static UAV includes the following sub-steps: S2.

1. Based on the concept of COP, calculate the COP of the j-th PLR user. The expression is: ； The total bandwidth allocated to PLR users is The bandwidth for RLR users is ,in and These are bandwidth allocation rate and total available bandwidth, respectively. Let be the distance between the UAV and the j-th ground user. It is the transmit power allocated to the j-th ground user. It is the transmit power allocated to the k-th ground user. It is the path loss exponent under the Loss of Path (LoS) condition. This is the channel power gain at a reference distance of one meter in this case. The reliability threshold is the minimum SINR required for legitimate users to meet reliability constraints. S2.2 Calculate the COP of the i-th RLR user, the expression is: ； in, It is the transmit power allocated to the i-th ground user. is the channel fading gain between the UAV and the i-th user, and v is the noise power; S2.

3. Based on the definition of SOP, the formula is derived. By using Using the probability generating function PGFL and Jensen's inequality, we obtain the upper bound of SOP: ； ； in, , Security threshold The radius of the confidential zone, H represents the density of eavesdroppers, and H represents the altitude of the drone. S2.

4. The condition for the j-th PLR user to achieve a positive confidentiality rate is derived as follows: ； in, , For the acceptable maximum DEP of expected reliability, the expected maximum transmit power of the j-th PLR user is: 。 2. The secure, ultra-reliable, and low-latency communication method in a UAV-supported NOMA wireless network according to claim 1, characterized in that: Step S1 includes the following sub-steps: S1.1 Considering air-to-ground communication via a UAV downlink wireless network, where multiple passive eavesdroppers exist on the ground, the hovering UAV serves two types of authorized users with different performance requirements: authorized users PLR who require privacy and low latency, and authorized users RLR who require reliability and low latency. UAV is equipped with There are one antenna for each ground node; the locations of authorized users and eve are determined by a density of [missing information]. and Two homogeneous Poisson point processes PPPs and Modeling; S1.

2. Obtain the SINR of PLR users, RLR users, and eavesdroppers using noise power; S1.3, introduced connection interruption probability and security interruption probability to evaluate channel quality; S1.

4. Utilize the eavesdropping code rates Rt and Rs to maximize the confidentiality rate.

3. The secure, ultra-reliable, and low-latency communication method in a UAV-supported NOMA wireless network according to claim 1, characterized in that: In step S3, based on the analysis framework of COP, SOP, and security rate, the problem of maximizing the security rate is solved by optimizing the eavesdropping code rate and the transmission power allocation, including the following sub-steps: S3.1 Given the UAV positioning altitude H, design the eavesdropping code rate. and The goal is to maximize the confidentiality rate while simultaneously satisfying performance levels of reliability and security; the problem of maximizing the confidentiality rate is expressed as: ； ； ； ； Consider this issue with the help of SIC. To perform confidentiality analysis, we obtain the COP and maximum bitrate of PLR users, then calculate the total COP of the j-th PLR user, and finally solve... ; S3.2, According to step S3.1, we get The optimal solution is: ； in, ; S3.3, By setting To obtain the optimal transmit power for the j-th PLR user, use This indicates that the total power allocated to other PLR users with stronger channel quality compared to the j-th PLR user is also set to be maximized; S3.4, combined with the power allocation given in step S3.3 to maximize the confidentiality rate of the j-th PLR user, introduces the concept of gradient descent in the algorithm process; According to the decision criteria, if the gradient of the function exceeds the expected accuracy, then the two power assignments mentioned above should be updated to... and Repeat the two power allocation update processes described above until the expected accuracy is achieved. Finally, step 3.4 yields the optimal power allocation for the j-th PLR user and other PLR users with better channel quality to maximize the safe rate.

4. The secure, ultra-reliable, and low-latency communication method in a UAV-supported NOMA wireless network according to claim 3, characterized in that: In step S4, the analysis of the COP, SOP, and STC of the dynamic UAV includes the following sub-steps: S4.1 Improve the reliability performance of authorized users. Suppose the i-th RLR user moves to the center of the secure zone, and the UAV flies within an inverted cone centered on the j-th PLR user with a maximum radius of D; the UAV flies freely in any direction within the space of the inverted cone; the cumulative distribution function CDF of the distance d between the center of the secure zone and the UAV is: ； And the probability density function PDF is: ； The COP for the j-th PLR user can be obtained as follows: ； Through constraints Maximum bitrate of dynamic drones The following is given: ； The optimal eavesdropping rate is: ； in For the expected maximum acceptable DEP, The acceptable minimum DEP for expected safety. This is the minimum safety requirement; S4.2, The condition for the j-th PLR user to obtain a positive confidentiality rate, derived from step S4.1, is as follows: ； Solve The problem of maximizing the security rate given a total power allocation is expressed as: ； in, For a finite block length, the global COP yields the following theorem, and the optimal solution is: ； By combining and , optimal get: ； The confidentiality rate of the j-th PLR user is the total power allocated to other PLR users at greater distances plus its own power. It is a monotonically increasing function; furthermore, given the constraint of power allocation to the j-th PLR user, for different total power allocations to maximize the security rate, τ is reformulated as: ； in, , .

5. The secure, ultra-reliable, and low-latency communication method in a UAV-supported NOMA wireless network according to claim 1, characterized in that: In step S5, the location of the wireless node and the message transmission process were simulated using MATLAB, mainly including the following sub-steps: S5.1 Based on the set network parameters, the locations of the drone and the authorized user PLR who requires privacy and low latency are considered in the context of network performance, thereby completing secure, ultra-reliable and low-latency communication in the wireless network, wherein the location of the drone is (H, 0, 0), and the j-th PLR user is located at (1, 0, 0). S5.2 Analyze the impact of different block lengths and noise power on interruption probability and decoding error probability; S5.3 Analyze how COP and SOP change as the noise power and total power of other PLR users are allocated; S5.4 Analyze the relationship between the security rate and transmission power and interference.

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