A kind of active-passive symbiosis covert communication method and system

Abstract

The present application relates to the technical field of wireless communication, and provides a kind of active-passive symbiosis covert communication method and system, and the power control method under fixed power is as follows: step one: monitor solves optimal detection threshold and minimum detection error probability to represent concealment using improved optimal hypothesis testing;Step two: according to the communication mode of hybrid transmitter, the effective throughput under fixed power is calculated;Step three: optimization parameter and solution.Random power control method is as follows: step 1: construct the random model of wireless radio frequency energy station transmitting power;Step 2: monitor solves optimal detection threshold and minimum detection error probability to represent concealment using improved optimal hypothesis testing;Step 3: calculate the expected effective throughput under random power;Step 4: optimization parameter and solution.The present application can make the communication behavior between legal communication equipment not be known by illegal third party, so as to ensure the security of communication.

Description

Technical Field

[0001] This invention relates to the field of wireless communication technology, and more specifically, to a method and system for active-passive symbiotic covert communication. Background Technology

[0002] In the field of communication technology today, energy-sustaining communication technologies, represented by wireless powered communication and passive backscatter communication, are considered key technologies supporting the widespread deployment and connectivity of ultra-large-scale small wireless devices in future 6G networks and realizing the Internet of Things, due to their unique advantage of collecting radio frequency signal energy from the environment to load and transmit information. These technologies have attracted widespread attention from academia and industry due to their potential for achieving sustainable communication.

[0003] However, existing passive communication technologies using passive backscattering have several limitations. This technology relies on ambient radio frequency (RF) signals, exhibits poor autonomy in message transmission, and suffers from lower transmission rates and lower reliability compared to active communication technologies. Specifically, when RF signals are lacking in the environment, passive communication technologies cannot utilize modulation techniques such as on-off keying (OOK) to load the information to be transmitted, resulting in message failure. Furthermore, the signal energy reflected by the backscattered tag is weak, exhibiting poor performance in terms of transmission reliability and rate, thus limiting its further application.

[0004] On the other hand, single active communication technologies powered by wireless technology also face many challenges. Their energy harvesting phase is too long, resulting in low spectrum utilization. Therefore, to overcome the limitations of the aforementioned technologies, a hybrid active-passive communication system based on radio frequency energy harvesting technology and passive backscatter communication has emerged. As a sustainable and energy-saving new paradigm, this system has become one of the most competitive IoT solutions. In this system, communication devices can autonomously select active or passive communication modes based on the harvested energy or the signal-to-interference-plus-noise ratio (SINR).

[0005] Existing active-passive coexistence communication mainly focuses on the transmission mode selection and switching scheme of the active-passive hybrid transmitter. Researchers have designed two mode selection protocols: a power threshold-based protocol (PTP) and a signal-to-noise ratio (SNR) threshold-based protocol (STP). In PTP mode, the hybrid transmitter first detects the available energy harvesting rate. If the energy harvesting rate is lower than the threshold required to power the RF transmitter circuitry (for active transmission), backscatter communication mode is used. Otherwise, active communication mode is adopted. In STP mode, the hybrid transmitter first attempts to transmit via backscatter. If the SNR achieved at the receiver is higher than the threshold required to decode information from the backscatter, the transmitter will be in ambient backscatter mode. Otherwise, it will switch to active communication mode. Subsequently, researchers proposed an adaptive selection and switching scheme based on a two-stage decision using energy-SNR awareness.

[0006] The aforementioned research on active-passive symbiotic communication focuses on the mode selection strategy of hybrid transmitters and the communication performance analysis under the proposed strategies, but it still suffers from low security. Malicious third parties can easily spy on users through open wireless media, leading to physical attacks. IoT devices, with limited capabilities and resources, cannot use stronger encryption protocols to mitigate this problem. Furthermore, in some scenarios, protecting the content of transmitted information is insufficient, as exposure of transmission activities may reveal the user's location or maliciously block the user's transmission. Examples include patient privacy data transmission in smart healthcare, intelligence exchange in military scenarios, and the transmission of critical transaction information in the financial sector. Summary of the Invention

[0007] The present invention provides a method and system for covert active-passive symbiotic communication, which enables the communication behavior between legitimate communication devices to remain unknown to unauthorized third parties, thereby ensuring the security of communication.

[0008] According to a method for active-passive symbiotic covert communication based on the present invention, it includes a power control method under fixed power and a power control method under random power.

[0009] The power control method under fixed power is as follows:

[0010] Step 1: The monitor uses an improved optimal hypothesis test to solve for the optimal detection threshold and the minimum detection error probability to characterize the stealth.

[0011] Step 2: Calculate the effective throughput at fixed power based on the communication mode of the hybrid transmitter;

[0012] Step 3: Optimize the parameters and solve for the goal of maximizing the total effective throughput of the system.

[0013] The power control method under random power is as follows:

[0014] Step 1: Construct a stochastic model of the transmit power of the wireless radio frequency power station;

[0015] Step 2: The monitor uses an improved optimal hypothesis test to solve for the optimal detection threshold and the minimum detection error probability to characterize the stealth.

[0016] Step 3: Calculate the expected effective throughput under random power;

[0017] Step 4: Optimize the parameters and solve for the goal of maximizing the total expected effective throughput of the system.

[0018] As a preferred option, step one specifically involves:

[0019] The monitor attempts to determine whether communication is occurring between the hybrid transceivers through observation-based hypothesis testing; the null hypothesis is then applied. Defined as hybrid transmitter silence, while assuming This indicates that the hybrid transmitter sent information to the receiver in backscatter mode, assuming... This indicates that the hybrid transmitter uses an active communication mode to send information to the receiver; the signals received by the monitor under three different assumptions are represented as follows:

[0020]

[0021] Among them, y w [i] represents the signal received by the monitor at time i, G is the energy beam gain, and P... t Let δ be the transmit power of the wireless radio frequency power station, δ∈[0,1] be the power reflection coefficient of the hybrid transmitter during backscatter communication, and h be the transmit power of the wireless radio frequency power station. tw This indicates the channel information from the transmitter to the monitor. and These are backscattered signals and active communication signals, respectively. This indicates that μ is the mean and σ is the mean. 2 The variance follows a complex Gaussian distribution. It is Gaussian white noise; P tA This refers to the transmit power of the hybrid transmitter in active communication mode, specifically expressed as follows: in ρ A This represents the circuit power consumption in active communication mode, ω is the energy harvesting duty cycle, and η∈(0,1] is the RF-DC power conversion efficiency; within a communication time slot, the observer's observation vector is represented as y. w =[yw [1],y w [2],...,y w [M]], where M is the block length;

[0022] Based on the above signal model, the following distribution is obtained:

[0023]

[0024] Where P0 = 0, P1 = δP t G, P2 = P tA , The variance of the noise received by the monitor, i.e., the noise power; The probability density function p of (j∈{0,1,2}) j (y w )for:

[0025]

[0026] Therefore, the joint probability density function of the observation vector Represented as:

[0027]

[0028] The ultimate goal of the monitor is to detect the existence of communication behavior; therefore, the latter two assumptions are combined, namely... These represent the presence or absence of transmission, respectively; the assumed prior probability is expressed as... The prior probability of transmission is expressed as: Therefore, the ratio of the posterior probabilities η(y) between the two hypotheses of existence and non-existence of communication is... w Written as:

[0029]

[0030] Furthermore, the maximum a posteriori probability criterion is adopted:

[0031]

[0032] in, and These refer to inferring whether transmission between the hybrid transceivers exists and does not exist, respectively; after algebraic transformation, the simplified form of the above decision expression is obtained:

[0033]

[0034] Among them, the test statistic T(y) w Let T(y) be the total received energy, and Γ be the power decision threshold. The monitor can then determine whether there is transmission based on the relationship between the total received energy and Γ. Furthermore, this formula shows that T(y) = Γ ...w Substitute Γ into η(y) w The value of Γ = 1 simplifies to Λ(Γ) = 0. Solving for this variance yields the optimal detection threshold Γ that minimizes the detector's error probability. * Λ(Γ) is defined as a function of the power decision threshold Γ as follows:

[0035]

[0036] T(y w Let be a random variable that follows a chi-square distribution with 2M degrees of freedom, and its conditional probability density function is:

[0037]

[0038] Where Γ(M)=(M-1)! is the gamma function, and M is the block length; furthermore, based on the above conditional probability density function and arbitrary decision threshold, the false alarm probability is... and the probability of missed detection They are respectively:

[0039]

[0040] in, For an incomplete gamma function, Let be the incomplete gamma function, where s represents the shape parameter and x represents the integration limit; therefore, the detection error probability is...

[0041] The optimal threshold Γ * Substitution Obtain the minimum detection error probability ξ * ;

[0042] Since the expression for the minimum detection error probability involves complex integrals, we further calculate the tight lower bound to obtain the KL divergence:

[0043]

[0044] in Represent two probability distributions and KL divergence, This represents the upper bound of the KL divergence obtained using logarithms and scaling.

[0045] Preferably, in step two, when the hybrid transmitter adopts backscatter communication mode, the received signal y at the hybrid receiver... B [i] is:

[0046]

[0047] Among them, htr This indicates the channel information from the transmitter to the receiver. It is white noise; when the hybrid transmitter adopts active communication mode, the signal y at the hybrid receiver is white noise. A [i] is:

[0048]

[0049] Effective throughput C e for:

[0050] C e =MR(1-θ),

[0051]

[0052] Where M is the block length, R is the channel coding rate, θ is the decoding error probability, and r represents the received signal-to-noise ratio. The Q-function represents the right-tail function of the standard normal distribution; the signal-to-noise ratios of backscattering and active communication modes are respectively... and Substituting the expression for effective throughput, we can obtain the effective throughput under both backscattering and active communication modes. and

[0053] Preferably, in step three, the optimization objective is to maximize the total effective throughput of the system, and the optimization parameter is to optimize the transmit power P of the wireless radio frequency power station. t Block length M, channel coding rate R in backscatter and active communication modes A and R B The optimization problem is represented as:

[0054] P1

[0055] stξ * ≥1-∈,

[0056] θ≤κ,

[0057]

[0058] M min ≤M≤M max ,

[0059] P t ≤P tmax ,

[0060] The first constraint represents the concealment constraint, where ε represents the preset concealment level to be achieved; the higher the minimum detection error probability of the monitor, the better the concealment performance of the system. The second constraint represents the transmission reliability constraint, where κ represents the preset decoding performance level to be achieved; the lower the decoding error probability of the receiver, the better. The third constraint represents the energy constraint in active communication mode. ρ A The first is the circuit power consumption in active communication mode; the fourth is the energy constraint in backscatter communication mode. ρ B The first is the circuit power consumption in backscattering mode; the fifth is the constraint on the range of block length values, M. min M represents the minimum value that M is allowed to take. max The sixth value represents the maximum value that M is allowed to achieve; the sixth value represents the transmit power constraint, P. tmax This indicates that P is allowed. t The maximum value obtained; based on the relationship of minimum detection error probability, the concealment constraint is rewritten in the following form to make the system more robust, satisfying the following optimization problem: the solution must satisfy P1:

[0061]

[0062] θ≤κ,

[0063]

[0064] M min ≤M≤M max ,

[0065] P t ≤P tmax ,

[0066] Next, the optimization problem is equivalently decomposed into two subproblems using a two-stage method; first, given the block length M, the transmit power P is... t Channel coding rate R in backscattering and active communication modes A and R B Optimize; then, within the feasible interval [M] min M max A one-dimensional search is performed within [the range] to further obtain the optimal M, where P is computed for each value of M. t R A and R B Through the above process, the global optimal solution P is obtained. t * , and M * This allows us to achieve the maximum total throughput.

[0067] Preferably, in step 1, the transmit power of the wireless radio frequency power station is set as a random variable that follows a uniform distribution, with the distribution being P. t ~U(P min ,P max ), P t probability density function f p (P t )for:

[0068]

[0069] As a preferred option, step 2 differs from step 1 in that T(y) w The conditional probability density function of () is:

[0070]

[0071]

[0072] make a=δG|h tw | 2 Substitution yields:

[0073]

[0074] Similarly, we can conclude that:

[0075]

[0076] in, The probabilities of false alarms and false misses are calculated using the maximum a posteriori decision:

[0077]

[0078] According to the formula for error detection probability The optimal decision threshold is obtained by minimizing ξ.

[0079] Preferably, in step 3, given the decoding error probability θ, the channel coding rate R is:

[0080]

[0081] Because P t ~U(P min ,P max Then, when the hybrid transmitter uses backscatter communication, the received signal-to-noise ratio of the legitimate receiver is... r B Substituting into the channel coding rate R above, we can obtain the channel coding rate Ri using the backscatter communication mode. B ;make Represent the desired channel coding rate and r in the desired backscatter communication mode, respectively.B If the probability density function is given, then:

[0082]

[0083] in:

[0084]

[0085] Similarly, based on the signal-to-noise ratio received by the legitimate receiver when the hybrid transmitter uses active communication... Determine the desired channel coding rate in active communication mode. By C e =MR(1-θ), thus obtaining in These represent the total expected effective throughput, the expected effective throughput in backscatter communication mode, and the expected effective throughput in active communication mode, respectively.

[0086] Preferably, in step 4, the parameter optimization aims to maximize the total expected effective throughput, i.e., to optimize the transmit power P of the wireless radio frequency power station. t Block length M, channel coding rate R in backscatter and active communication modes A and R B The optimization problem is represented as:

[0087]

[0088] stξ * ≥1-∈,

[0089]

[0090] M min ≤M≤M max .

[0091] The power of the wireless radio frequency power station is inversely proportional to the minimum error detection probability of the monitor and directly proportional to the effective throughput; therefore, P max It is inversely proportional to the minimum error detection probability of the monitor and directly proportional to the effective throughput; therefore, the solution to the optimization problem is:

[0092]

[0093] M * =M max

[0094] For ξ * =1-ε.

[0095] This invention provides an active-passive symbiotic covert communication system, which employs the aforementioned active-passive symbiotic covert communication method.

[0096] The beneficial effects of this invention are as follows:

[0097] This invention employs fixed power control and random power control strategies to achieve covert transmission while ensuring the system's energy self-sufficiency. This not only effectively resolves the contradiction between covertness and energy supply in traditional active-passive symbiotic communication systems, but also significantly improves the overall performance and practicality of the system.

[0098] In terms of energy self-sufficiency, a fixed power control strategy provides a stable energy supply for the system, ensuring that communication equipment can maintain basic communication functions under various environmental conditions. A stochastic power control strategy, on the other hand, further optimizes energy utilization efficiency by dynamically adjusting power output, enabling the system to achieve higher communication performance while meeting energy self-sufficiency requirements.

[0099] In terms of covert transmission, the random power control strategy dynamically adjusts the power output, making the communication signal exhibit randomness in both the frequency and time domains, thereby effectively reducing the risk of detection. In this way, the present invention can achieve highly reliable and highly covert communication transmission in complex electromagnetic environments.

[0100] In summary, the active-passive symbiotic covert communication method proposed in this invention, through the innovative adoption of fixed power control and random power control strategies, not only demonstrates excellent performance in energy self-sustainability and covert transmission, but also ensures that the system achieves positive effective throughput while satisfying covert constraints. This provides a novel approach and solution for the design of future communication systems. This invention not only has significant theoretical implications but also broad practical application prospects, and is expected to be widely used in multiple fields such as the Internet of Things, military communications, and smart grids. Attached Figure Description

[0101] Figure 1 This is a flowchart of the power control method under fixed power in the embodiment;

[0102] Figure 2 This is a flowchart of the power control method under random power in the embodiment;

[0103] Figure 3 This is a schematic diagram of the active-passive symbiotic covert communication system in the embodiment. Detailed Implementation

[0104] To further understand the content of this invention, a detailed description of the invention will be provided in conjunction with the accompanying drawings and embodiments. It should be understood that the embodiments are merely illustrative and not limiting of the invention.

[0105] Example

[0106] This embodiment provides a method for covert active-passive symbiotic communication, including power control methods under fixed power and random power. It is applicable to secure communication in active-passive symbiotic communication systems. The active-passive symbiotic covert communication system mentioned in this embodiment includes: a power beacon (PB) responsible for providing power to the active-passive communication system; a hybrid transmitter acting as the signal source, with both active and passive communication modes, capable of energy harvesting and using the relationship between the power received from the power beacon and the communication mode activation power threshold to select between active and backscatter communication; and a hybrid receiver receiving and decoding the signal. An unauthorized third party, such as a radiometer, monitors whether the hybrid transceivers are communicating. The hybrid transceivers share a key unknown to the eavesdropper, including specific communication times, encoding / decoding methods, etc. Figure 3 As shown.

[0107] like Figure 1 As shown, the power control method under fixed power is as follows:

[0108] Step 1: The monitor uses an improved optimal hypothesis test to solve for the optimal detection threshold and the minimum detection error probability to characterize the concealment (in order to simplify the calculation and ensure that the final optimization problem can obtain a closed-form solution, this embodiment derives the KL (Kullback-Leibler) divergence to obtain the lower bound of the minimum detection error probability to characterize the concealment).

[0109] Step one specifically involves:

[0110] The monitor attempts to determine whether communication is occurring between the hybrid transceivers through observation-based hypothesis testing; the null hypothesis is then applied. Defined as hybrid transmitter silence, while assuming This indicates that the hybrid transmitter sent information to the receiver in backscatter mode, assuming... This indicates that the hybrid transmitter uses an active communication mode to send information to the receiver; the signals received by the monitor under three different assumptions are represented as follows:

[0111]

[0112] Among them, y w [i] represents the signal received by the monitor at time i, G is the energy beam gain, and P... t Let δ be the transmit power of the wireless radio frequency power station, δ∈[0,1] be the power reflection coefficient of the hybrid transmitter during backscatter communication, and h be the transmit power of the wireless radio frequency power station. tw This indicates the channel information from the transmitter to the monitor. and These are backscattered signals and active communication signals, respectively. This indicates that μ is the mean and σ is the mean.2 The variance follows a complex Gaussian distribution. It is Gaussian white noise; P tA This refers to the transmit power of the hybrid transmitter in active communication mode, specifically expressed as follows: in ρ A This represents the circuit power consumption in active communication mode, ω is the energy harvesting duty cycle, and η∈(0,1] is the RF-DC power conversion efficiency; within a communication time slot, the observer's observation vector is represented as y. w =[y w [1],y w [2],...,y w [M]], where M is the block length;

[0113] Based on the above signal model, the following distribution is obtained:

[0114]

[0115] Where P0 = 0, P1 = δP t G, P2 = P tA , The variance of the noise received by the monitor, i.e., the noise power; The probability density function for (j∈{0,1,2}) is:

[0116]

[0117] Therefore, the joint probability density function of the observation vectors is expressed as:

[0118]

[0119] The ultimate goal of the monitor is to detect the existence of communication behavior; therefore, the latter two assumptions are combined, namely... These represent the presence or absence of transmission, respectively; the assumed prior probability is expressed as... The prior probability of transmission is expressed as: Therefore, the ratio of the posterior probabilities between the two hypotheses of existence and non-existence of communication can be written as:

[0120]

[0121] Furthermore, the maximum a posteriori probability criterion is adopted:

[0122]

[0123] in, and These refer to inferring whether transmission between the hybrid transceivers exists and does not exist, respectively; after algebraic transformation, the simplified form of the above decision expression is obtained:

[0124]

[0125] Among them, the test statistic T(y) w Let T(y) be the total received energy, and Γ be the power decision threshold. The monitor can then determine whether transmission has occurred based on the relationship between the total received energy and Γ. Furthermore, this formula shows that T(y)... w Substitute Γ into η(y) w The value of Γ = 1 simplifies to Λ(Γ) = 0. Solving for this variance yields the optimal detection threshold Γ that minimizes the detector's error probability. * Λ(Γ) is defined as a function of the power decision threshold Γ as follows:

[0126]

[0127] T(y w Let be a random variable that follows a chi-square distribution with 2M degrees of freedom, and its conditional probability density function is:

[0128]

[0129] Where Γ(M)=(M-1)! is the gamma function, and M is the block length; furthermore, based on the above conditional probability density function and any decision threshold, the probabilities of false alarms and false misses are respectively:

[0130]

[0131] in, For an incomplete gamma function, Let be the incomplete gamma function, where s represents the shape parameter (real number) and x represents the integration limit (non-negative real number); therefore, the detection error probability is .

[0132] The optimal threshold Γ * Substitution Obtain the minimum detection error probability ξ * ;

[0133] Since the expression for the minimum detection error probability involves complex integrals, we further calculate the tight lower bound to obtain the KL divergence:

[0134]

[0135] in Represent two probability distributions and KL divergence, This represents the upper bound of the KL divergence obtained using logarithms and scaling.

[0136] Step 2: Calculate the effective throughput under fixed power based on the communication mode of the hybrid transmitter.

[0137] In step two, when the hybrid transmitter uses backscatter communication mode, the received signal at the hybrid receiver is:

[0138]

[0139] Among them, h tr This indicates the channel information from the transmitter to the receiver. Also known as white noise; when the hybrid transmitter uses active communication mode, the signal at the hybrid receiver is:

[0140]

[0141] Effective throughput is:

[0142] C e =MR(1-θ),

[0143]

[0144] Where M is the block length, R is the channel coding rate, θ is the decoding error probability, and r represents the received signal-to-noise ratio. The Q-function represents the right-tail function of the standard normal distribution; the signal-to-noise ratios of backscattering and active communication modes are respectively... and Substituting the expression for effective throughput, we can obtain the effective throughput under both backscattering and active communication modes. and

[0145] Step 3: Optimize the parameters and solve for the goal of maximizing the total effective throughput of the system.

[0146] In step three, the optimization objective is to maximize the total effective throughput of the system, and the optimization parameter is to optimize the transmit power P of the wireless radio frequency power station. t Block length M, channel coding rate R in backscatter and active communication modes A and R B The optimization problem is represented as:

[0147]

[0148] stξ * ≥1-∈,

[0149] θ≤κ,

[0150]

[0151] M min ≤M≤M max ,

[0152] P t ≤P tmax ,

[0153] The first constraint represents the concealment constraint, where ε represents the preset concealment level (a smaller ε value indicates a higher concealment requirement), and a higher minimum detection error probability for the monitor indicates better concealment performance. The second constraint represents the transmission reliability constraint, where κ represents the preset decoding performance level, and a lower decoding error probability for the receiver is better. The third constraint represents the energy constraint in active communication mode. ρ A The first is the circuit power consumption in active communication mode; the fourth is the energy constraint in backscatter communication mode. ρ B The first is the circuit power consumption in backscattering mode; the fifth is the constraint on the range of block length values, M. min M represents the minimum value that M is allowed to take. max The sixth value represents the maximum value that M is allowed to achieve; the sixth value is the transmit power constraint, P. tmax This indicates that P is allowed. t The maximum value obtained. Based on the relationship of minimum detection error probability, the concealment constraint is rewritten in the following form to make the system more robust, satisfying the following optimization problem: The solution must satisfy P1:

[0154]

[0155] θ≤κ,

[0156]

[0157] M min ≤M≤M max ,

[0158] P t ≤P tmax ,

[0159] Next, various optimization algorithms can be selected for solving the problem. Taking the two-stage method as an example, the optimization problem is equivalently decomposed into two subproblems; first, given the block length M, the transmit power P... t Channel coding rate R in backscattering and active communication modes A and R B Optimize; then, within the feasible interval [M] min M max A one-dimensional search is performed within [the range] to further obtain the optimal M, where P is computed for each value of M.t R A and R B Through the above process, the global optimal solution P is obtained. t * , and M * This allows us to achieve the maximum total throughput.

[0160] like Figure 2 As shown, the power control method under random power is as follows:

[0161] Step 1: Construct a stochastic model of the transmit power of the wireless radio frequency power station.

[0162] The transmit power of the wireless radio frequency power station is set as a random variable that follows a uniform distribution, with the distribution being P. t ~U(P min ,P max ), P t The probability density function is:

[0163]

[0164] Step 2: The monitor uses an improved optimal hypothesis test to solve for the optimal detection threshold and the minimum detection error probability to characterize the concealment.

[0165] The difference between step 2 and step 1 is that T(y) w The conditional probability density function of is:

[0166] make a=δG|h tw | 2 Substitution yields:

[0167]

[0168] Similarly, we can conclude that:

[0169]

[0170] in, The probabilities of false alarms and false misses are calculated using the maximum a posteriori decision:

[0171]

[0172] According to the formula for error detection probability The optimal decision threshold is obtained by minimizing ξ.

[0173] Step 3: Calculate the expected effective throughput under random power.

[0174] In step 3, given the decoding error probability θ, the channel coding rate is:

[0175]

[0176] Because P t ~U(P min ,P max Then, when the hybrid transmitter uses backscatter communication, the received signal-to-noise ratio of the legitimate receiver is... r B Substituting into the channel coding rate R above, we can obtain the channel coding rate Ri using the backscatter communication mode. B .make Represent the desired channel coding rate and r in the desired backscatter communication mode, respectively. B If the probability density function is given, then:

[0177]

[0178] in:

[0179]

[0180] Similarly, based on the signal-to-noise ratio received by the legitimate receiver when the hybrid transmitter uses active communication... The desired channel coding rate in active communication mode can be obtained. By C e =MR(1-θ), thus obtaining in These represent the total expected effective throughput, the expected effective throughput in backscatter communication mode, and the expected effective throughput in active communication mode, respectively.

[0181] Step 4: Optimize the parameters and solve for the goal of maximizing the total expected effective throughput of the system.

[0182] In step 4, the optimization objective is to maximize the total expected effective throughput of the system, and the optimization parameter is the transmit power P of the wireless radio frequency power station. t Block length M, channel coding rate R in backscatter and active communication modes A and R B The optimization problem is represented as:

[0183]

[0184] stξ * ≥1-∈,

[0185]

[0186] M min ≤M≤M max .

[0187] The power of the wireless radio frequency power station (signal-to-noise ratio at the monitor) is inversely proportional to the monitor's minimum error detection probability and directly proportional to the effective throughput; therefore, P max It is inversely proportional to the minimum error detection probability of the monitor and directly proportional to the effective throughput; therefore, the solution to the optimization problem is:

[0188]

[0189] M * =M max

[0190] For ξ * =1-ε.

[0191] This embodiment can be further extended to discrete random power. Active communication modes have multiple fixed transmit powers, or backscatter communication modes have multiple power reflection coefficients, thus extending the ternary hypothesis testing to a multivariate hypothesis testing. If only the existence of communication is detected, non-zero hypotheses can be accumulated for analysis similar to a ternary hypothesis. If the transmit power level needs to be further identified, the maximum a posteriori probability criterion can be used for decision-making, yielding the optimal decision threshold and the corresponding decision interval.

[0192] This embodiment provides an active-passive symbiotic covert communication system, which adopts the above-described active-passive symbiotic covert communication method.

[0193] This embodiment ensures that the communication activities between legitimate communication devices are not known to unauthorized third parties, thereby guaranteeing the security of communication.

[0194] The present invention and its embodiments have been described above illustratively. This description is not restrictive, and the figures shown are only one embodiment of the present invention; the actual structure is not limited thereto. Therefore, if those skilled in the art are inspired by this description and design similar structures and embodiments without departing from the spirit of the present invention, such designs should fall within the protection scope of the present invention.

Claims

1. A method for covert active-passive symbiotic communication, characterized in that: This includes power control methods under fixed power and power control methods under random power. The power control method under fixed power is as follows: Step 1: The monitor uses an improved optimal hypothesis test to solve for the optimal detection threshold and the minimum detection error probability to characterize the stealth. Step one specifically involves: The monitor attempts to determine whether communication is occurring between the hybrid transceivers through observation-based hypothesis testing; the null hypothesis is then applied. Defined as hybrid transmitter silence, while assuming This indicates that the hybrid transmitter sent information to the receiver in backscatter mode, assuming... This indicates that the hybrid transmitter uses an active communication mode to send information to the receiver; the signals received by the monitor under three different assumptions are represented as follows: ； in, Indicates the time when the monitor is Received signal, For energy beam gain, The transmit power of the wireless radio frequency power station. Power reflection coefficient for backscatter communication using a hybrid transmitter. This indicates the channel information from the transmitter to the monitor. and These are backscattered signals and active communication signals, respectively. Indicates The mean, The variance follows a complex Gaussian distribution. It is Gaussian white noise; This refers to the transmit power of the hybrid transmitter in active communication mode, specifically expressed as follows: ,in , This refers to the circuit power consumption in active communication mode. It is the duty cycle of energy harvesting. This refers to the radio frequency to DC power conversion efficiency; within a communication time slot, the observer's observation vector is represented as... , The length of the block; Based on the above signal model, the following distribution is obtained: ； in, , , , The variance of the noise received by the monitor, i.e., the noise power; probability density function for: ； Therefore, the joint probability density function of the observation vector Represented as: ； The ultimate goal of the monitor is to detect the existence of communication behavior; therefore, the latter two assumptions are combined, namely... , These represent the presence or absence of transmission, respectively; the assumed prior probability is expressed as... The prior probability of transmission is expressed as: Therefore, the ratio of the posterior probabilities between the two hypotheses of existence and non-existence of communication. Written as: ； Furthermore, the maximum a posteriori probability criterion is adopted: ； in, and These refer to inferring whether transmission between the hybrid transceivers exists and does not exist, respectively; after algebraic transformation, the simplified form of the above decision expression is obtained: ； Among them, the test statistic In order to receive the total energy, It is a power decision threshold; the monitor can then base its decision on the total received energy and... The relationship determines whether transmission has occurred; and from this formula, it can be seen that... Substitution That is, simplify to Solving for this variance yields the optimal detection threshold that minimizes the detector's error probability. ,in Defined as follows regarding the power decision threshold Functions: ； Is it subject to the degree of freedom? The conditional probability density function of a random variable with a chi-square distribution is: ； in, For gamma function, Let the block length be denoted; then, based on the aforementioned conditional probability density function and any decision threshold, the false alarm probability is calculated. and the probability of missed detection They are respectively: ； in, For an incomplete gamma function, Let be the lower incomplete gamma function, where Indicates shape parameters, This represents the integration limit; therefore, the probability of a detection error is... ; Optimal threshold Substitution To obtain the minimum detection error probability ; Since the expression for the minimum detection error probability involves complex integrals, we further calculate the tight lower bound to obtain the KL divergence: ； in Represent two probability distributions and KL divergence, This represents the upper bound of the KL divergence obtained using logarithmic scaling; Step 2: Calculate the effective throughput at fixed power based on the communication mode of the hybrid transmitter; Step 3: Optimize the parameters and solve for the goal of maximizing the total effective throughput of the system; The power control method under random power is as follows: Step 1: Construct a stochastic model of the transmit power of the wireless radio frequency power station; In step 1, the transmit power of the wireless radio frequency power station is set as a random variable that follows a uniform distribution, the distribution of which is as follows: , probability density function for: ； Step 2: The monitor uses an improved optimal hypothesis test to solve for the optimal detection threshold and the minimum detection error probability to characterize the stealth. Step 3: Calculate the expected effective throughput under random power; Step 4: Optimize the parameters and solve for the goal of maximizing the total expected effective throughput of the system.

2. The active-passive symbiotic covert communication method according to claim 1, characterized in that: In step two, when the hybrid transmitter adopts backscatter communication mode, the received signal at the hybrid receiver... for: ； in, This indicates the channel information from the transmitter to the receiver. It is white noise; when the hybrid transmitter adopts active communication mode, the signal at the hybrid receiver is white noise. for: ； Effective throughput for: ； in, For block length, For channel coding rate, This represents the probability of decoding errors. Indicates the received signal-to-noise ratio. express Q The function, namely the right-tail function of the standard normal distribution; the signal-to-noise ratio of backscattering and active communication modes, respectively. and Substituting the expression for effective throughput, we can obtain the effective throughput under both backscattering and active communication modes. and .

3. The active-passive symbiotic covert communication method according to claim 2, characterized in that: In step three, the optimization objective is to maximize the total effective throughput of the system, and the optimization parameter is to optimize the transmit power of the wireless radio frequency power station. Block length Channel coding rate in backscattering and active communication modes and The optimization problem is represented as: ； The first constraint represents a hidden constraint. The first represents the preset required level of concealment; the higher the minimum probability of detection error for the monitor, the better the system's concealment performance. The second represents the transmission reliability constraint. The first represents the preset required decoding performance, where a lower decoding error probability for the receiver is better; the second represents the energy constraint in active communication mode. , The first is the circuit power consumption in active communication mode; the fourth is the energy constraint in backscatter communication mode. , The fifth is the circuit power consumption in backscattering mode; the sixth is the constraint on the range of block length values. Indicates permission The minimum value obtained, Indicates permission The maximum value obtained; the sixth is the transmit power constraint. Indicates permission The maximum value obtained; based on the relationship of minimum detection error probability, the concealment constraint is rewritten in the following form to make the system more robust, satisfying the following optimization problem: the solution must satisfy P1: ； Next, the optimization problem is equivalently decomposed into two subproblems using a two-phase method; first, given the block length... Below, regarding the transmission power Channel coding rate in backscatter and active communication modes and Optimize; then, within the feasible range A one-dimensional search is performed within the inner dimension to further obtain the optimal solution. Among them, for Calculate each value , and Through the above process, the global optimal solution is obtained. , , and This allows for the attainment of the maximum total throughput.

4. The active-passive symbiotic covert communication method according to claim 3, characterized in that: Step 2 differs from Step 1 in that... The conditional probability density function is: ； ； make Substitution yields: ； Similarly, we can conclude that: ； in, The probabilities of false alarms and false misses are calculated using the maximum a posteriori decision method: ； According to the formula for error detection probability By minimizing This yields the optimal decision threshold.

5. The active-passive symbiotic covert communication method according to claim 4, characterized in that: In step 3, if a given decoding error probability is given... Channel coding rate for: ； because Then, when the hybrid transmitter uses backscatter communication, the received signal-to-noise ratio of the legitimate receiver is... ;Will Substitute the above channel coding rate The channel coding rate using the backscatter communication mode can then be obtained. ;make Represent the desired channel coding rate and respectively in the desired backscatter communication mode. If the probability density function is given, then: ； in: ； ； Similarly, based on the signal-to-noise ratio received by the legitimate receiver when the hybrid transmitter uses active communication... To obtain the expected channel coding rate in active communication mode. ;Depend on get ,in These represent the total expected effective throughput, the expected effective throughput in backscatter communication mode, and the expected effective throughput in active communication mode, respectively.

6. The active-passive symbiotic covert communication method according to claim 5, characterized in that: In step 4, with the goal of maximizing the total expected effective throughput, the parameters are optimized, namely, the transmit power of the wireless radio frequency power station. Block length Channel coding rate in backscattering and active communication modes and The optimization problem is represented as: ； The power of the wireless radio frequency power station is inversely proportional to the minimum error detection probability of the monitor and directly proportional to the effective throughput; therefore, It is inversely proportional to the minimum error detection probability of the monitor and directly proportional to the effective throughput; therefore, the solution to the optimization problem is:

7. A covert active-passive symbiotic communication system, comprising a processor, characterized in that: The processor is used to execute a passive-active symbiotic covert communication method as described in any one of claims 1-6.

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