Limited block length secure transmission method and system based on communication perception integration

Abstract

The invention discloses a finite block length secure transmission method and system based on communication perception integration, and relates to the technical field of communication. Comprising the following steps: S1, constructing a system model, determining an optimization problem, analyzing a safe transmission rate capable of reaching a limited block length, and constructing a safe rate maximization problem; s2, designing an optimization scheme: decomposing the non-convex optimization problem in the S1 into three sub-problems, namely uplink transmission power distribution of IoE equipment, sensing signal design and joint sensing and communication receiving beam forming optimization, converting each sub-problem into a solvable convex optimization problem, and respectively solving the solvable convex optimization problem, and obtaining the solution of the original problem through an alternate iteration method until the algorithm converges or reaches the maximum iteration times. According to the method, a potential threat source is identified more accurately by utilizing a sensing data auxiliary system, and the technologies of beam forming, artificial noise and the like are utilized, so that the secure transmission between legal users is ensured, the quality of a received signal of an eavesdropper is reduced, and the secure fusion of a communication function and a sensing function is realized.

Description

Technical Field

[0001] The present invention belongs to the field of communication technology, and more specifically, relates to a limited block length secure transmission method and system based on communication perception integration. Background Art

[0002] The advent of the Sixth Generation Mobile Communications (6G) technology marks a significant leap forward in innovation. In this transformative era, the Internet of Everything (IoE), a key technology, aims to connect people, machines, and objects in the physical world into a seamless intelligent network. However, as the IoE ecosystem expands, the demand for ultra-low latency, high reliability, large-scale connectivity, and stringent security is surging. At the same time, accurate and efficient perception capabilities, such as environmental monitoring, object detection, and positioning, are becoming crucial. To this end, Integrated Sensing and Communications (ISAC) technology has emerged. 6G-enabled ISAC systems are expected to improve spectrum efficiency, enhance security, reduce infrastructure costs, and support new applications that rely on real-time environmental perception and data exchange.

[0003] The combination of ISAC and non-orthogonal multiple access (NOMA) is an effective solution to address spectrum congestion and inter-device interference caused by the proliferation of IoE devices. ISAC leverages the dual-functionality of wireless signals to enable both perception and communication within the same frequency band, improving spectral efficiency. NOMA, on the other hand, supports multi-user access through power-domain resource sharing, significantly outperforming traditional orthogonal multiple access (OMA) in spectral efficiency. Furthermore, limited block length transmission is crucial for IoE applications with stringent latency and reliability requirements. The combination of NOMA and ISAC provides a flexible resource allocation solution for ultra-reliable, low-latency, limited block length transmission. Another potential benefit of ISAC lies in its ability to detect and mitigate security threats through its perception capabilities. Leveraging the inherent characteristics of wireless channels, ISAC-supported physical layer security technologies enable confidential transmission without the need for complex upper-layer encryption. However, the joint optimization of perception and communication tasks, resource allocation, and security assurance requirements pose significant challenges to system design and implementation. Summary of the Invention

[0004] To meet the low-latency and secure transmission requirements of the Internet of Everything (IoE), this method proposes a finite block length secure transmission framework for ISAC systems based on uplink NOMA. This framework employs a triple-function base station that simultaneously performs uplink signal reception, potential eavesdropper detection, and active jamming signal transmission. Taking into account the imperfect cancellation of inter-function and inter-device interference, a "finite block length secure transmission rate" is proposed as a security performance metric. To optimize security performance and effectively utilize sensing capabilities, the finite block length secure transmission rate is maximized while ensuring perceptual quality by jointly optimizing the uplink transmit power, the base station receive combining matrix, the transmission of sensing signals, and the transmission of artificial noise. Because the performance penalty terms caused by decoding errors and information leakage in finite block length transmission make the problem highly coupled and strictly non-convex, this method proposes an approximate method to convert the finite block length secure transmission rate into a tractable form and designs an iterative solution method based on alternating optimization until the algorithm converges or reaches a maximum number of iterations.

[0005] To solve the above technical problems, the technical solution adopted by the present invention is: a limited block length secure transmission method based on communication perception integration, comprising the following steps:

[0006] S1. Build a system model and determine the optimization problem

[0007] Build an ISAC system model that supports uplink NOMA. Based on the constructed ISAC system model, analyze the achievable secure transmission rate with a finite block length and formulate the secure rate maximization problem.

[0008] S2. Design optimization plan

[0009] The highly coupled non-convex optimization problem constructed in step S1 is decomposed into three sub-problems: uplink transmission power allocation of IoE devices, perception signal design, and joint perception and communication receive beamforming optimization. Each sub-problem is converted into a solvable convex optimization problem using an approximate method or an approximate method plus a semidefinite relaxation method, and each sub-problem is solved separately. The solution to the original problem is obtained through alternating iterations until the algorithm converges or the maximum number of iterations is reached.

[0010] Preferably, in step S1, the ISAC system model includes a t Uniform Linear Array (ULA) transmitting antennas and N r A triple-function base station (TFBS) with K ULA receiving antennas also contains K single-antenna communication devices and a sensing target that is also a potential single-antenna eavesdropper, which attempts to eavesdrop on the confidential information transmitted by the single-antenna communication devices;

[0011] In addition to receiving and decoding signals sent by single-antenna communication devices, TFBS also detects potential eavesdroppers by actively transmitting sensing signals; the set of single-antenna communication devices is defined as

[0012] Preferably, in step S1, the decoding order is: the TFBS first treats the communication signal as interference to decode the perception signal, and then decodes the communication signal after eliminating the perception signal; the specific steps are as follows:

[0013] The communication channel, eavesdropping channel, artificial noise interference channel, and perception echo channel from the single-antenna communication device k to the base station are represented by h k,d 、h k,e 、h J and A(θ0); from the perspective of perception, TFBS emits a perceptual waveform And receive the radar echo reflected by the target; through the target reflection, TFBS can obtain target information; In addition, assuming u J At the same time, it acts as an interference signal to reduce the received signal-to-interference-and-noise ratio (SINR) of potential eavesdroppers; through the receive beamformer TFBS detects target reflection from the superimposed communication and perception signals. The received target reflection intensity is:

[0014]

[0015] in is the complex amplitude of the target, which is mainly determined by the round-trip path loss and radar cross section, based on the transmitted sensing waveform u J definition To ensure that the TFBS correctly decodes the target reflection signal and extracts information, the SINR of the target reflection must meet the threshold constraint:

[0016]

[0017] where σ 2 represents the noise power, Γ r Indicates the minimum SINR value that needs to be met for TFBS to correctly decode the perceived signal;

[0018] From the communication perspective, TFBS receives signals from IoE devices; the signal symbol transmitted by single-antenna communication device k is x k , the transmission power is p k ,satisfy and After receiving the superimposed communication signal, TFBS uses receive beamforming To detect the signal x of the single-antenna communication device k kTFBS first treats the communication signal as interference to detect the target reflection signal, then subtracts and eliminates the radar echo from the received signal, and the remaining part is used for communication signal detection; signal x k The SINR can be expressed as

[0019]

[0020] in is interference from undecoded device signals, It is the residual interference caused by the imperfect elimination of Inter-Function-Interference (IFI) and Inter-Device-Interference (IDI). and They represent the elimination coefficients of inter-function interference and inter-device interference respectively; indicates perfect inter-function interference cancellation, means perfect interference cancellation between devices, represents imperfect inter-function interference cancellation, represents imperfect inter-device interference cancellation, while Indicates that no inter-function interference elimination is performed. Indicates that no inter-device interference elimination is performed;

[0021] Potential eavesdroppers will also try to intercept the signal transmitted by the device. The signal x received by the eavesdropper k The SINR can be expressed as

[0022]

[0023] in Indicates the interference caused to the eavesdropper by the artificial noise actively sent by the base station;

[0024] Given a code block length L k , tolerable decoding error probability ε k , information leakage probability δ k,e , received signal-to-interference-and-noise ratio γ k and eavesdropping signal-to-interference-and-noise ratio γ k,e In this case, the device can be obtained The finite block length secure transmission rate is

[0025]

[0026] in and is the channel dispersion, which measures the random variability of the channel relative to a deterministic channel with the same capacity, Q -1 [·] represents the Gaussian Q function The inverse function; only when R k >0 to ensure safe transmission;

[0027] By jointly optimizing the device's transmit power, transmit sensing signal design, and full-duplex base station receive beamforming, the secure short packet transmission rate can be maximized, which can be expressed in the following mathematical form:

[0028]

[0029] Among them, (C1) and (C2) are the maximum power constraints, P k,max and P J are the maximum transmit powers of the device and base station, (C3) and (C4) represent the receive beamforming constraints, and (C5) represents the minimum SINR value Γ that TFBS needs to meet for correctly decoding the perceived signal. r .

[0030] Furthermore, the finite block length secure transmission rate in equation (5) is rewritten as follows:

[0031]

[0032] where η k =1+γ k ∈(1,+∞) and η k,e =1+γ k,e ∈(1,+∞) is an auxiliary variable defined; for a given transmission block length L k , decoding error probability ε k and information leakage probability δ k,e ,parameter and can be regarded as a constant, and ι k >0 and ι k,e >0;

[0033] Using the first-order Taylor expansion, the finite block length secure transmission rate can be approximated as

[0034]

[0035] in It is to facilitate the writing of the constructed auxiliary functions. represents the first-order derivative of g(η), represents a feasible point; it can be shown that It is R k (η k ,η k,e ) is the lower bound of .

[0036] Preferably, in step S2, the uplink transmission power of the IoE device is allocated as follows:

[0037] For a fixed perception signal u J , receive beam w k and w s , the relaxed uplink transmit power allocation problem can be expressed as:

[0038]

[0039] (P1) is a non-convex problem; introduce slack variables v = {v1,…,v K} and v e ={v 1,e ,…,v K,e}, where each element satisfies v k ≤η k , and v k,e ≥η k,e , Substituting into the optimization function, the optimization function can be rewritten as Solve the relaxed optimization problem and obtain an approximate solution to the original maximization problem; introduce the constraints into the objective function and construct the Lagrangian function of the original problem as follows:

[0040]

[0041] The power allocation optimization method based on Lagrangian duality is as follows:

[0042]

[0043] Preferably, the perception signal design is as follows:

[0044] For a fixed transmit power p and receive beam w k and w s , the relaxed perception signal design problem is expressed as:

[0045]

[0046] make in satisfy Tr(U J )≤P J and Rank(U J )=1;

[0047] Introduce slack variables q={q1,…,q K} and q e ={q 1,e ,…,q K,e}, where each element satisfies

[0048]

[0049] in Represents residual interference plus noise; further dealing with the non-convexity of the optimization problem, the following function is defined

[0050]

[0051] H2(q k,e ,U J )=q k,e [Tr(U J H J )+σ 2 ](13b)

[0052] And use the first-order Taylor expansion to relax into the following form

[0053]

[0054] By ignoring the rank-one constraint, the optimization problem (P2) is transformed into a solvable convex optimization problem, which is solved using the toolkit CVX. The rank-one constraint can be restored using the Gaussian randomization method.

[0055] Preferably, the joint sensing and communication receive beamforming optimization is specifically as follows:

[0056] For a given transmit power p and sensing signal u J , the optimization problem can be expressed as

[0057]

[0058] make Then there is

[0059] in make Then there is

[0060]

[0061] At the same time, the following constraints are met: Tr(W k )=1,Rank(W k )=1, Tr(W s )=1,Rank(W s )=1;

[0062] The eavesdropper's received SINRγ k With receive beamforming W k and W s The part of the objective function related to the eavesdropping rate can be ignored, and the variable η k =1+γ kRewrite it as follows:

[0063]

[0064] To deal with η k The non-convexity of , introduce the slack variable m={m1,…,m K}, where each element satisfies the constraint m k ≤η k , In order to further deal with the non-convexity of the optimal objective function, the following function is defined:

[0065]

[0066] And H4(W k ) is approximately in the following form:

[0067]

[0068] By ignoring the rank-one constraint, the optimization problem (P3) is transformed into a solvable convex optimization problem, which is solved using the toolkit CVX. The rank-one constraint can be restored using the Gaussian randomization method.

[0069] Preferably, the joint optimization algorithm based on alternating iteration is specifically as follows:

[0070] In each iteration, the transmit power allocation, sensing signal design, and sensing and communication receive beamforming design of the IoE device are optimized alternately. The starting point of each iteration is the solution of the previous iteration. Ultimately, when the algorithm converges, a high-quality suboptimal solution to the initial optimization problem is obtained, which can be summarized as follows:

[0071]

[0072]

[0073] A secure transmission system with limited block length based on integrated communication and perception, including a triple-functional base station, an IoE device, and a perception target, i.e., a passive eavesdropper;

[0074] The triple-function base station receives uplink transmission signals, detects potential eavesdroppers, and transmits active interference signals. Receiving uplink transmission signals includes receiving signals from IoE devices and sensing echo signals when detecting potential eavesdroppers. All signals are superimposed in the NOMA manner, and the receiving end uses the serial interference cancellation (SIC) method to identify and decode all signals. SIC is divided into two orders: communication-centric and perception-centric. The communication-centric method first regards the communication signal as an interference signal, decodes and eliminates the sensing echo signal, and then decodes the communication signal; the perception-centric method first regards the sensing echo signal as an interference signal, decodes and eliminates the communication signal, and then decodes the sensing echo signal. Detecting potential eavesdroppers means that the base station actively transmits a sensing signal and receives the corresponding echo signal, thereby determining whether there is a potential eavesdropping threat in the surrounding environment. The active interference signal and the sensing signal transmitted by the triple-function base station are the same signal.

[0075] The IoE device sends a finite block length coded signal to the base station, and the signals of multiple devices share time and frequency resources and superimpose in the power domain through the NOMA method;

[0076] The sensing target attempts to steal confidential information sent from IoE devices but does not actively transmit any signals.

[0077] The beneficial effect of adopting the above technical solution is that this method solves the problem of confidential information transmitted by IoE devices being at risk of leakage due to the open nature of the wireless environment. With the theory of intrinsic security at the physical layer as the core, a secure transmission framework for an integrated perception and communication system based on uplink non-orthogonal multiple access is designed, and ultra-reliable low-latency service quality is achieved based on finite block length coding theory. The system uses perception data to more accurately identify potential threat sources, and utilizes technologies such as beamforming and artificial noise to ensure secure transmission between legitimate users while reducing the quality of the received signal for eavesdroppers, thereby achieving a secure integration of communication and perception functions. BRIEF DESCRIPTION OF THE DRAWINGS

[0078] Figure 1 It is a technical structure diagram;

[0079] Figure 2 It is a schematic diagram of the algorithm flow;

[0080] Figure 3 It is a finite block length secure transmission model based on communication and perception integration;

[0081] Figure 4 It is a simulation Figure 1 ;

[0082] Figure 5It is a simulation Figure 2

[0083] Figure 6 It is a simulation Figure 3 DETAILED DESCRIPTION

[0084] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0085] In combination with the development trend of 6G communication perception integration and the performance requirements and research objectives of limited block length secure transmission, the present invention discloses a limited block length secure transmission system based on ISAC, which includes: a triple-function base station, an IoE device, and a perception target (passive eavesdropper).

[0086] A triple-function base station can simultaneously perform three functions: receiving uplink transmission signals, detecting potential eavesdroppers, and transmitting active jamming signals. The uplink transmission signal reception function of a triple-function base station includes receiving signals from IoE devices and sensing echo signals from potential eavesdroppers. All signals are superimposed using the NOMA method, and the receiver uses Successive Interference Cancellation (SIC) to identify and decode all signals. SIC can be categorized into two approaches: communication-centric and perception-centric. The former first treats the communication signal as an interference signal, decodes and cancels the sensing echo signal, and then decodes the communication signal. The latter first treats the sensing echo signal as an interference signal, decodes and cancels the communication signal, and then decodes the sensing echo signal. The triple-function base station detects potential eavesdroppers by actively transmitting a sensing signal and receiving the corresponding echo signal to determine whether there is a potential eavesdropping threat in the surrounding environment. The active jamming signal transmitted by the triple-function base station and its actively transmitted sensing signal are actually the same signal. This multiplexing mechanism reduces energy consumption.

[0087] The IoE device sends a finite block length coded signal to the base station, and the signals of multiple devices share time and frequency resources and superimpose in the power domain through NOMA.

[0088] The sensing target is actually a potential passive eavesdropper that attempts to steal confidential information sent from IoE devices but does not actively transmit any signals.

[0089] By jointly designing the base station's triple functionality and optimizing the transmit power of IoE devices, we aim to maximize the finite block length secure transmission rate while ensuring perceived quality, thereby improving security performance. This paper proposes an approximation method to convert the finite block length secure transmission rate into a more manageable form due to its strict non-convexity and high degree of multivariate coupling. Figure 1 A technical structure diagram is given. Figure 2 The algorithm flow chart is given.

[0090] The method disclosed in the present invention is divided into the following two steps: S1: Construct a system model and determine the optimization problem: Construct an ISAC system model that supports uplink NOMA, including a triple-function base station, multiple devices equipped with single antennas, and a sensing target (i.e., a potential eavesdropper). Based on the constructed system model, analyze the achievable secure transmission rate of a finite block length and construct a security rate maximization problem; S2: Design an optimization scheme: Decompose the highly coupled non-convex optimization problem constructed in step one into three sub-problems (uplink transmission power allocation of IoE devices, sensing signal design, and joint sensing and communication receiving beamforming optimization), and convert each sub-problem into a solvable convex optimization problem through an approximate method (or an approximate method plus a semidefinite relaxation method), and solve them separately, and obtain the solution to the original problem through an alternating iterative method until the algorithm converges or reaches the maximum number of iterations. The detailed process is as follows:

[0091] S1, build a system model and determine the optimization problem.

[0092] Consider an ISAC-supported uplink NOMA system that consists of an N t Uniform Linear Array (ULA) transmitting antennas and N r A triple-function base station (TFBS) with multiple ULA receiving antennas. Figure 3 As shown in the figure, there are K single-antenna communication devices in the system, and a sensing target that is also a potential single-antenna eavesdropper, which attempts to eavesdrop on the confidential information transmitted by the device. The device set is defined as

[0093] In addition to receiving and decoding the signals sent by the device, TFBS also detects potential eavesdroppers by actively transmitting sensing signals. These sensing signals also serve as interference signals, which are used to reduce the quality of the received signal of potential eavesdroppers. To achieve better secure communication performance, the system adopts the following decoding sequence: TFBS first decodes the sensing signal by treating the communication signal as interference, and then decodes the communication signal after eliminating the sensing signal. The communication channel, eavesdropping channel, artificial noise interference channel, and sensing echo channel from device k to the base station are represented by h and h, respectively.k,d 、h k,e 、h J and A(θ0).

[0094] From a perceptual perspective, TFBS emits perceptual waveforms And receive the radar echo reflected by the target. Through the target reflection, TFBS can obtain target information (such as direction and distance). In addition, assuming u J At the same time, it acts as an interference signal to reduce the received signal-to-interference-and-noise ratio (SINR) of potential eavesdroppers. TFBS detects target reflection from the superimposed communication and perception signals. The received target reflection intensity is:

[0095]

[0096] in is the complex amplitude of the target, which is mainly determined by the round-trip path loss and radar cross section, based on the transmitted sensing waveform u J definition To ensure that the TFBS correctly decodes the target reflection signal and extracts information, the SINR of the target reflection must meet the threshold constraint:

[0097]

[0098] where σ 2 represents the noise power, Γ r It represents the minimum SINR value that TFBS needs to meet to correctly decode the perceived signal.

[0099] From the communication perspective, TFBS receives signals from IoE devices. The signal symbol transmitted by device k is x k , the transmission power is p k ,satisfy and After receiving the superimposed communication signal, TFBS uses receive beamforming To detect the signal x of device k k TFBS first treats the communication signal as interference to detect the target reflection signal, then subtracts and eliminates the radar echo from the received signal, and the remaining part is used for communication signal detection. k The SINR can be expressed as

[0100]

[0101] in is interference from undecoded device signals, It is the residual interference caused by the imperfect elimination of Inter-Function-Interference (IFI) and Inter-Device-Interference (IDI). and denote the elimination coefficients of inter-function interference and inter-device interference, respectively. More specifically, (or ) indicates perfect inter-function interference (or inter-device interference) cancellation, (or ) indicates imperfect inter-function interference (or inter-device interference) cancellation, while (or ) indicates that no inter-function interference (or inter-device interference) elimination is performed.

[0102] A potential eavesdropper will also try to intercept the signal transmitted by the device. The signal x received by the eavesdropper k The SINR can be expressed as

[0103]

[0104] in It indicates the interference caused to the eavesdropper by the artificial noise actively sent by the base station.

[0105] To meet the strict latency constraints of certain mission-critical IoT applications, finite block length transmission is considered. However, due to insufficient averaging of thermal noise and channel distortion, there will be performance loss compared to long packet transmission. k , tolerable decoding error probability ε k , information leakage probability δ k,e , received signal-to-interference-and-noise ratio γ k and eavesdropping signal-to-interference-and-noise ratio γ k,e In this case, the device can be obtained The finite block length secure transmission rate is

[0106]

[0107] in and is the channel dispersion, which measures the random variability of the channel relative to a deterministic channel with the same capacity, Q -1 [·] represents the Gaussian Q function The inverse function of k >0 to ensure secure transmission.

[0108] To effectively utilize the sensing capabilities of TFBS to achieve system security, we aim to maximize the secure short packet transmission rate by jointly optimizing the device's transmit power, transmit sensing signal design, and the full-duplex base station's receive beamforming. This can be expressed in the following mathematical form:

[0109]

[0110] Among them, (C1) and (C2) are the maximum power constraints, P k,max and P J are the maximum transmit powers of the device and base station, (C3) and (C4) represent the receive beamforming constraints, and (C5) represents the minimum SINR value Γ that TFBS needs to meet for correctly decoding the perceived signal. r .

[0111] S2, design optimization plan.

[0112] It can be seen that (P) is a strictly non-convex optimization problem due to the non-convexity of the objective function and the constraints. In addition, the highly coupled optimization variables {p,u J ,w k ,w s} makes it difficult to obtain the global optimal solution. Therefore, this method develops an algorithm based on alternating optimization (AO) to find high-quality suboptimal solutions. First, an approximation method is proposed to rewrite the finite block length secure transmission rate in Equation (5) into the following more tractable form:

[0113]

[0114] where η k =1+γ k ∈(1,+∞) and η k,e =1+γ k,e ∈(1,+∞) is an auxiliary variable defined. For a given transmission block length L k , decoding error probability ε k and information leakage probability δ k,e ,parameter and can be regarded as a constant, and ι k >0 and ι k,e >0.

[0115] Using the first-order Taylor expansion, the finite block length secure transmission rate can be approximated as

[0116]

[0117] in It is to facilitate the writing of the constructed auxiliary functions. represents the first-order derivative of g(η), represents a feasible point. It can be proved that It is R k (η k ,η k,e ) is the lower bound of .

[0118] 1) Uplink transmission power allocation of IoE devices

[0119] For a fixed perception signal u J , receive beam w k and w s , the relaxed uplink transmit power allocation problem can be expressed as:

[0120]

[0121] However, (P1) is still a difficult non-convex problem. Introducing slack variables v = {v1,…,v K} and v e ={v 1,e ,…,v K,e}, where each element satisfies v k ≤η k , and v k,e ≥η k,e , Substituting into the optimization function, the optimization function can be rewritten as By solving the relaxed optimization problem, we can get an approximate solution to the original maximization problem. By introducing the constraints into the objective function, we can construct the Lagrangian function of the original problem as follows

[0122]

[0123] The power allocation optimization method based on Lagrangian duality is as follows:

[0124]

[0125]

[0126] 2) Perception signal design

[0127] For a fixed transmit power p and receive beam w k and w s , the relaxed perception signal design problem can be expressed as:

[0128]

[0129] To transform this optimization problem into a more tractable form, let in satisfy Tr(U J )≤P J and Rank(U J )=1.

[0130] Furthermore, the slack variable q={q1,…,q K} and q e ={q 1,e ,…,q K,e}, where each element satisfies

[0131]

[0132] in Represents residual interference plus noise. In order to further deal with the non-convexity of the optimization problem, the following function is defined

[0133]

[0134] H2(q k,e ,U J )=q k,e [Tr(U J H J )+σ 2 ](13b)

[0135] And use the first-order Taylor expansion to relax into the following form

[0136]

[0137]

[0138] By ignoring the rank-one constraint, the optimization problem (P2) can be transformed into a solvable convex optimization problem, which can be solved using the CVX toolkit. The rank-one constraint can be restored using the Gaussian randomization method.

[0139] 3) Joint perception and communication receive beamforming optimization

[0140] For a given transmit power p and sensing signal u J , the optimization problem can be expressed as

[0141]

[0142] First, reformulate the optimization problem into a more tractable form. Let Then there is in Similarly, let Then there is And the following constraints need to be met: Tr(W k )=1,Rank(Wk )=1, Tr(W s )=1,Rank(W s )=1.

[0143] It can be seen that the eavesdropper's receiving SINRγ k With receive beamforming W k and W s Therefore, the part of the objective function related to the eavesdropping rate can be ignored, and the variable η k =1+γ k It can be rewritten as follows:

[0144]

[0145] To deal with η k The non-convexity of , introduce the slack variable m={m1,…,m K}, where each element satisfies the constraint m k ≤η k , In order to further deal with the non-convexity of the optimal objective function, the following function is defined:

[0146]

[0147]

[0148] And H4(W k ) is approximately in the following form:

[0149]

[0150] By ignoring the rank-one constraint, the optimization problem (P3) can be transformed into a solvable convex optimization problem, which can be solved using the CVX toolkit. The rank-one constraint can be restored using the Gaussian randomization method.

[0151] 4) Joint optimization algorithm based on alternating iteration

[0152] To perform joint optimization, we propose an algorithm based on alternating optimization to maximize the secure transmission rate for finite block lengths. Specifically, in each iteration, we alternately optimize the transmit power allocation of IoE devices, the sensing signal design, and the sensing and communication receive beamforming design. Each iteration starts with the solution from the previous iteration. Ultimately, when the algorithm converges, a high-quality suboptimal solution to the initial optimization problem is obtained. This is summarized as follows:

[0153]

[0154] The effects of the examples of the present invention can be further illustrated through simulation.

[0155] In the simulation, the parameters are set as follows: noise power is -104dBm, path loss coefficient is -20dB, average target response strength is 1 / 20, the number of IoE devices is 2, the number of transmit and receive antennas of the base station is 16 each, the transmission block length is 1000, and the tolerable decoding error probability is 10 -5 , the tolerable information leakage probability is 10 -5 , the residual coefficient of inter-functional interference is 10 -3 , the residual coefficient of interference between devices is 10 -3 In order to illustrate the superiority of the proposed scheme, the following comparison algorithm is introduced:

[0156] Comparative Algorithm 1: Improves security performance by maximizing the achievable rate under the eavesdropper SINR constraint, using the weighted minimum mean square error-semidefinite relaxation method.

[0157] Comparison Algorithm 2: Orthogonal Multiple Access: The sensing capability and communication capability are independent of each other. The sensing signal and the communication signal occupy different spectrum resources, and there is no need to consider inter-function interference.

[0158] Comparison Algorithm 3: The base station has no sensing capability and cannot detect the presence of potential eavesdroppers. The optimization goal is to maximize the achievable finite block length transmission rate.

[0159] Figure 4 The relationship between the achievable secure transmission rate for finite block lengths and the number of transmit and receive antennas is plotted. The number of transmit and receive antennas is always equal. Clearly, as the number of antennas increases, the achievable secure rate for all schemes improves. Using more antennas allows the system to better exploit spatial diversity, thereby reducing the likelihood of eavesdropping. Furthermore, a larger number of antennas enables beamforming, which focuses the transmitted signal energy more closely in a specific, desired direction, resulting in even greater performance improvements. This not only improves communication efficiency but also reduces signal leakage outside the intended reception area, thereby enhancing security. In OMA systems, although increasing the number of antennas can also lead to some performance improvements, the inherent orthogonality constraints of OMA limit the potential for such improvements, resulting in a relatively slow rate increase.

[0160] Figure 5The impact of transmission block length on security performance is demonstrated, and the achievable secure rate for infinite block length transmission is characterized under the condition of perfect elimination of inter-function interference. As the transmission block length increases, noise and interference in the channel are more effectively averaged, reducing their impact on information transmission. Therefore, as the transmission block length increases, the system can recover the original information with a higher probability of accuracy, thereby improving the achievable secure rate and gradually approaching the secure rate for infinite block length transmission. However, it is worth noting that while long packet transmission can increase the achievable secure rate, it also introduces additional transmission delay. Therefore, in practical applications, the relationship between transmission block length and achievable rate needs to be balanced according to the specific application scenario and requirements. In low-latency and high-reliability communications, finite block length transmission may be a better choice.

[0161] Figure 6 The relationship between the tolerable probability of error decoding, the tolerable probability of information leakage, and the effective security rate is shown, where the effective security rate is obtained by multiplying the achievable security rate with the reliability factor and the security factor, that is, (1-ε k )(1-δ k,e )R k Under the premise of ensuring a certain level of security, as the tolerable probability of decoding errors increases, the achievable secure rate increases, which comes at the expense of reduced reliability. Similarly, under the premise of ensuring a certain level of reliability, a lower tolerable probability of information leakage means stricter requirements for security, which will lead to a decrease in the achievable secure rate. Therefore, when the achievable secure rate is multiplied by the coefficients of reliability and security, the effective secure rate may show a trend of first increasing and then decreasing, which reflects the inherent contradiction between reliability, security and transmission efficiency. Therefore, in order to achieve overall performance optimization, it is necessary to consider the above factors.

[0162] The above are only preferred specific embodiments of the present invention, but the scope of protection of the present invention is not limited thereto. Any technician familiar with this technical field, within the technical scope disclosed by the present invention, who makes equivalent replacements or changes based on the technical solutions and inventive concepts of the present invention, should be covered by the scope of protection of the present invention.

Claims

1. A secure transmission method with limited block length based on integrated communication and perception, characterized in that: The following steps are involved: S1. Build a system model and determine the optimization problem; Build an ISAC system model that supports uplink NOMA. Based on the constructed ISAC system model, analyze the achievable secure transmission rate with a finite block length and formulate the secure rate maximization problem. S2, design optimization plan; The highly coupled non-convex optimization problem constructed in step S1 is decomposed into three sub-problems: uplink transmission power allocation of IoE devices, perception signal design, and joint perception and communication receive beamforming optimization. Each sub-problem is converted into a solvable convex optimization problem using an approximate method or an approximate method plus a semidefinite relaxation method, and each sub-problem is solved separately. The solution to the original problem is obtained through alternating iterations until the algorithm converges or the maximum number of iterations is reached.

2. The method for secure transmission of limited block length based on integrated communication and perception according to claim 1, characterized in that: The ISAC system model consists of a t uniform linear array (ULA) transmitting antennas and N r A triple-function base station (TFBS) with ULA receiving antennas also contains K single-antenna communication devices and a sensing target that is also a potential single-antenna eavesdropper, which attempts to eavesdrop on confidential information transmitted by the single-antenna communication devices; In addition to receiving and decoding signals sent by single-antenna communication devices, TFBS also detects potential eavesdroppers by actively transmitting sensing signals; the set of single-antenna communication devices is defined as 3. The method for secure transmission of limited block length based on integrated communication and perception according to claim 2, characterized in that: In step S1, the decoding order is: TFBS first treats the communication signal as interference to decode the perception signal, and then decodes the communication signal after eliminating the perception signal. The specific steps are as follows: The communication channel, eavesdropping channel, artificial noise interference channel, and perception echo channel from the single-antenna communication device k to the base station are represented by h k,d 、h k,e 、h J and A(θ0); from the perspective of perception, TFBS emits a perceptual waveform And receive the radar echo reflected by the target; through the target reflection, TFBS can obtain target information; In addition, assuming u J At the same time, it acts as an interference signal to reduce the received signal-to-interference-and-noise ratio (SINR) of potential eavesdroppers; through the receive beamformer TFBS detects target reflection from the superimposed communication and perception signals. The received target reflection intensity is: in is the complex amplitude of the target, which is determined by the round-trip path loss and radar cross section, based on the transmitted sensing waveform u J definition To ensure that the TFBS correctly decodes the target reflection signal and extracts information, the SINR of the target reflection must meet the threshold constraint: where σ 2 represents the noise power, Γ r Indicates the minimum SINR value that needs to be met for TFBS to correctly decode the perceived signal; TFBS receives signals from IoE devices; the signal symbol transmitted by single-antenna communication device k is x k , the transmission power is p k ,satisfy and After receiving the superimposed communication signal, TFBS uses receive beamforming To detect the signal x of the single-antenna communication device k k TFBS first treats the communication signal as interference to detect the target reflection signal, then subtracts and eliminates the radar echo from the received signal, and the remaining part is used for communication signal detection; signal x k The SINR can be expressed as in is interference from undecoded device signals, It is the residual interference caused by the imperfect cancellation of inter-functional interference IFI and inter-device interference IDI. and They represent the elimination coefficients of inter-function interference and inter-device interference respectively; indicates perfect inter-function interference cancellation, means perfect interference cancellation between devices, represents imperfect inter-function interference cancellation, represents imperfect inter-device interference cancellation, while Indicates that no inter-function interference elimination is performed. Indicates that no inter-device interference elimination is performed; Potential eavesdroppers will also try to intercept the signal transmitted by the device. The signal x received by the eavesdropper k The SINR is expressed as in Indicates the interference caused to the eavesdropper by the artificial noise actively sent by the base station; Given a code block length L k , tolerable decoding error probability ε k , information leakage probability δ k,e , received signal-to-interference-and-noise ratio γ k and eavesdropping signal-to-interference-and-noise ratio γ k,e In the case of The finite block length secure transmission rate is in and is the channel dispersion, which measures the random variability of the channel relative to a deterministic channel with the same capacity, Q -1 [·] represents the Gaussian Q function The inverse function; only when R k >0 to ensure safe transmission; By jointly optimizing the device's transmit power, transmit sensing signal design, and full-duplex base station receive beamforming, the secure short packet transmission rate can be maximized, which can be expressed in the following mathematical form: Among them, (C1) and (C2) are the maximum power constraints, P k,max and P J are the maximum transmit powers of the device and base station, (C3) and (C4) represent the receive beamforming constraints, and (C5) represents the minimum SINR value Γ that TFBS needs to meet for correctly decoding the perceived signal. r .

4. The method for secure transmission of limited block length based on communication and perception integration according to claim 3, characterized in that: The finite block length secure transmission rate in equation (5) is rewritten as follows: where η k =1+γ k ∈(1,+∞) and η k,e =1+γ k,e ∈(1,+∞) is an auxiliary variable defined; for a given transmission block length L k , decoding error probability ε k and information leakage probability δ k,e ,parameter and can be regarded as a constant, and ι k >0 and ι k,e >0; Using the first-order Taylor expansion, the finite block length secure transmission rate can be approximated as in It is to facilitate the writing of the constructed auxiliary functions. represents the first-order derivative of g(η), represents a feasible point; it can be shown that It is R k (η k ,η k,e ) is the lower bound of .

5. The method for secure transmission of limited block length based on integrated communication and perception according to claim 4, characterized in that: In step S2, the uplink transmission power of the IoE device is allocated as follows: For a fixed perception signal u J , receive beam w k and w s , the relaxed uplink transmit power allocation problem is expressed as: (P1) is a non-convex problem; introduce slack variables v = {v1,…,v K } and v e ={v 1,e ,…,v K,e }, where each element satisfies and Substituted into the optimization function, the optimization function is rewritten as Solve the relaxed optimization problem and obtain an approximate solution to the original maximization problem; introduce the constraints into the objective function and construct the Lagrangian function of the original problem as follows:

6. The method for secure transmission of limited block length based on communication and perception integration according to claim 4, characterized in that: The perception signal design is as follows: For a fixed transmit power p and receive beam w k and w s , the relaxed perception signal design problem is expressed as: make in Meet U J ≥0, Tr(U J )≤P J and Rank(U J )=1; Introduce slack variables q={q1,…,q K } and q e ={q 1,e ,…,q K,e }, where each element satisfies in Represents residual interference plus noise; further dealing with the non-convexity of the optimization problem, the following function is defined H2(q k,e ,U J )=q k,e [Tr(U J H J )+σ 2 ](13b) And use the first-order Taylor expansion to relax into the following form By ignoring the rank-one constraint, the optimization problem (P2) is transformed into a solvable convex optimization problem, which is solved using the toolkit CVX and the rank-one constraint is restored using the Gaussian randomization method.

7. The method for secure transmission of limited block length based on integrated communication and perception according to claim 4, characterized in that: The joint perception and communication receive beamforming optimization is as follows: For a given transmit power p and sensing signal u J , the optimization problem is expressed as make Then there is in make Then there is At the same time, the following constraints are met: k ≥0, Tr(W k )=1,Rank(W k )=1,W s ≥0, Tr(W s )=1,Rank(W s )=1; The eavesdropper's received SINRγ k With receive beamforming W k and W s The part of the objective function related to the eavesdropping rate can be ignored, and the variable η k =1+γ k Rewrite it as follows: To deal with η k The non-convexity of , introduce the slack variable m={m1,…,m K }, where each element satisfies the constraint In order to further deal with the non-convexity of the optimal objective function, the following function is defined: And H4(W k ) is approximately in the following form: By ignoring the rank-one constraint, the optimization problem (P3) is transformed into a solvable convex optimization problem, which is solved using the toolkit CVX and the rank-one constraint is restored using the Gaussian randomization method.

8. The method for secure transmission with limited block length based on integrated communication and perception according to claim 4, characterized in that: The joint optimization algorithm based on alternating iteration is as follows: In each iteration, the transmit power allocation, sensing signal design, and sensing and communication receive beamforming design of the IoE device are optimized alternately. The starting point of each iteration is the solution of the previous iteration. Ultimately, when the algorithm converges, a high-quality suboptimal solution to the initial optimization problem is obtained.

9. A secure transmission system with limited block length based on integrated communication and perception, characterized in that: It includes triple-function base stations, IoE devices, and sensing targets, i.e., passive eavesdroppers; The triple-function base station receives uplink transmission signals, detects potential eavesdroppers, and transmits active interference signals. Receiving uplink transmission signals includes receiving signals from IoE devices and sensing echo signals from detecting potential eavesdroppers. All signals are superimposed in the NOMA method, and the receiving end uses the serial interference cancellation (SIC) method to identify and decode all signals. SIC has two sequences: communication-centric and perception-centric. The communication-centric method first treats the communication signal as an interference signal, decodes and eliminates the sensing echo signal, and then decodes the communication signal. The perception-centric method first treats the sensing echo signal as an interference signal, decodes and eliminates the communication signal, and then decodes the sensing echo signal. Detecting potential eavesdroppers means the base station actively transmits sensing signals and receives corresponding echo signals to determine whether there is a potential eavesdropping threat in the surrounding environment. The active interference signal and the sensing signal transmitted by the triple-function base station are the same signal; IoE devices send finite block length coded signals to the base station, and the signals of multiple devices share time and frequency resources and superimpose in the power domain through NOMA. The sensing target attempts to steal confidential information sent from IoE devices but does not actively transmit any signals.

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