CN115915139A - Intelligent reflector assisted unequal prior probability covert communication method - Google Patents
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Abstract
The invention belongs to the technical field of information security of wireless communication networks, and relates to an intelligent reflector assisted unequal prior probability covert communication method a And transmitting the codeword length L to maximize the effective throughput eta of the communication link between the transmitting end and the receiving end when the eavesdropper performs detection with the optimal detection threshold, and providing the optimal first effective throughput for realizing the maximum effective throughputThe transmission probability is checked. The invention solves the optimal power detection threshold of the eavesdropper under unequal prior probability to realize optimal detection, and provides the optimal transmitting power, the optimal code word length and the optimal prior transmission probability of the intelligent reflector-assisted covert communication under the limiting condition of covert communication under the condition that the eavesdropper is the most unfavorable for both sides of the legitimate communication.
Description
Technical Field
The invention belongs to the technical field of information security of wireless communication networks, and relates to an intelligent reflector assisted unequal prior probability covert communication method, in particular to an effective throughput of a communication link maximized by jointly optimizing transmitting power and transmitting code word length by an information source.
Background
With the continuous and deep research on wireless communication technology, a fifth generation communication system is developed at a high speed, compared with a 1G cellular network, the communication rate is greatly improved, a complex and huge wireless communication network is being constructed, and a large amount of information is transmitted through a wireless network, wherein the information comprises some confidential information, such as personal identity information, bank account information, various passwords and the like. However, the wireless communication channel has a wide propagation characteristic, information is very easy to eavesdrop, even if the information is encrypted, the mode or flow of information transmission may cause information leakage and serious loss, and thus, great concern is raised about the security of wireless communication.
Different from the information encryption technology and the modern information hiding technology, the hidden communication is a very promising technology, and aims to utilize uncertainty of transmitting power, a channel and the like of a transmitting end to generate interference on an eavesdropper, so that the eavesdropper cannot correctly judge whether legal transmission behaviors are happening, the wireless communication safety problem is fundamentally solved, and high-level safety is kept. At present, foreign research teams have derived and verified the basic theory about covert communication, and Bash et al propose a famous square root law, which gives the upper limit of communication capacity under AWGN channel conditions. The intelligent reflecting surface can carry out phase shift adjustment on incident signals through a reflecting element on the surface so as to reconfigure a propagation environment, and the monitoring performance of an eavesdropper can be deteriorated while the legal communication quality is enhanced through reasonably designing the reflection coefficient of the intelligent reflecting surface, so that the intelligent reflecting surface is widely applied to covert communication.
At present, most covert communication work assumes that prior probabilities of whether a transmitting end selects to transmit information are equal, and the influence of a data packet generation process on the prior probabilities is ignored. In some practical communication scenarios, such as real-time condition monitoring systems, to meet the low latency requirement, condition data packets are randomly generated and transmitted in a timely manner. The generation of data packets is controlled by the poisson process, and studies have given an upper limit of data packets that can implement covert communication within a certain time interval and sufficient conditions on the rate of the poisson process. The limited transmission time of the current data packet has a significant influence on the generation of the next data packet, so that the prior transmission probability in covert communication is greatly influenced and is influenced by the transmission of the data packet, and the prior probability is not necessarily the best choice for realizing the maximum effective throughput.
The invention provides a specific strategy for carrying out unequal prior probability covert communication by using an intelligent reflecting surface, and a model schematic diagram is shown in figure 1. By optimizing the phase shift matrix theta of the intelligent reflecting surface, the signal-to-interference-and-noise ratio at the legal receiving end is maximized, and the transmitting power P is jointly optimized under the condition of meeting the concealment condition a And the length L of the transmission code word, so that the effective throughput eta of a communication link between the transmitting end and the receiving end is maximized when an eavesdropper detects the eavesdropper by using the optimal detection threshold, and the optimal prior transmission probability for realizing the maximum effective throughput is given.
Disclosure of Invention
The object of the invention is to enable covert communication while maximizing the effective throughput of the communication link. Considering that communication is carried out in a complex urban environment, obstacles are dense, so that ground transmission attenuation is overlarge, and the signal intensity of a receiving end is very small. Based on the situation, the intelligent reflecting surface is designed to maximize the signal intensity of the receiving end by adjusting the signal phase. In a communication network equipped with a single-antenna transmitting terminal, a single-antenna receiving terminal, a single-antenna eavesdropper and an intelligent reflecting surface, the eavesdropper is set to detect the existence of legal communication by using the optimal power detection threshold value of the eavesdropper, and on the basis, P is jointly optimized a And L to ensure thatThe method ensures that the hidden communication can be still realized under the condition that an eavesdropper selects the most unfavorable situation for both parties of the legal communication, and simultaneously, the effective throughput eta of a communication link is maximized.
The technical scheme adopted by the invention for solving the technical problems is as follows:
an intelligent reflector assisted unequal prior probability covert communication method comprises the following steps:
firstly, constructing a system model:
1) The transmitting end (Alice) and the legitimate receiving end (Bob) are in legitimate communication, which communication fact is expected not to be detected by an eavesdropper (Willie). By arranging the intelligent reflecting surface with M reflecting elements, signals received by Bob and Willie are superposed by signals transmitted by a direct ground link and signals transmitted by a reflecting link of the intelligent reflecting surface.
2) In this model, a three-dimensional space is considered, and a specific schematic diagram is fig. 1. The communication channel between Alice and Bob and the eavesdropping channel between Alice and Willie are both a superposition of large-scale fading and Rayleigh fading distributions
Wherein beta is 0 ，α，h e Respectively representing the power gain at each 1m reference distance, the large-scale fading factor and the random distribution parameter of the Rayleigh channel, wherein h e Obedience mean 0 and variance beta e Complex gaussian distribution of e = ab, aw, d k And k ∈ { ab, aw } represents the distance between nodes. The channel from Alice to the intelligent reflecting surface is the superposition of large-scale fading and Rayleigh fading distribution>
The channels from the intelligent transmitting surface to Bob and Willie are also the superposition of large-scale fading and Rayleigh fading profiles->
Wherein h is I And g m M = B, W are M × 1 and 1 × M matrices characterizing rayleigh fading, respectively, d j And k is equal to { ai, ib, iw } to represent the intelligent reflecting surface-to-ground sectionThe distance between the points. Considering additive white Gaussian noise, and->
The noise power at Willie and Bob respectively. Alice sends Gaussian information sequence x [ i],i＝1,2,...,L。
3) Transmitting power P of transmitting terminal Alice a Not exceeding the upper power limit P max The length L of the transmitted code word does not exceed the upper limit L of the code word length max 。
4) Let R denote the information transfer rate between Alice and Bob:
wherein gamma is b Is the signal to interference and noise ratio at Bob,
called the Q function, also called the right tail function of the standard normal distribution, Q -1 (x) Is the inverse of the Q function, and δ represents the average error probability of decoding at Bob.
5) The prior probability of Alice at each transmission cycle can be given by modeling the arrival of a packet at this event as a poisson process with a rate λ:
ρ 1 ＝1-e -λT (2)
ρ 0 ＝1-ρ 1 ＝e -λT (3)
where ρ is 1 Means the probability of Alice selecting the transmission signal, ρ 0 Representing the probability that Alice chooses to remain silent.
Given a rate λ, the a priori transmission probability is determined only by the packet transmission duration T. For a packet transmission duration T, the bandwidth of the transmission system is B, which can be rewritten as:
6) It is known that in communications with limited transmitted codeword length, the average error probability of decoding at the receiving end cannot be neglected, and based on (1), the effective throughput η from the transmitting end to the legitimate receiving end can be given:
η＝ρ 1 R(1-δ) (5)
secondly, listing an optimization problem according to the system model:
1) To determine whether legitimate communication behavior exists, willie's binary hypothesis test is as follows:
willie wants to adopt the best detection scheme to minimize its average probability of false detection. May be based on maximum likelihood criteria
Obtaining optimal power detection threshold gamma * . Willie compares the received signal power, as measured by the power detector radiometer, with Γ * To determine the communication between Alice and Bob. And when the power of the received signal is greater than a preset detection threshold, judging that the communication behavior occurs, otherwise, judging that the communication behavior does not occur.
2) In order to ensure the implementation of covert communication, a restriction condition of covert communication needs to be given:
where epsilon is the tolerance value. Further scaling the relative entropy to obtain a final concealment constraint expression,
3) For any given transmit power P a And transmission codeword length L, optimal
The goal of (c) is always to maximize the received signal strength at Bob. I.e. require +>
The die length of (a) is maximized due to h ab Is a complex scalar, there is a phase angle, <' > is>
Is also a complex scalar quantity, as long as g B Θh I And h ab Is the same, so that->
The die length of (a) is maximized. Therefore, the best phase can be obtained:
θ n ＝arg(h ab )-arg(g B ,n)-arg(h I ,n) (10)
where arg (a) is the phase angle of a complex scalar a, g B N and h I N represents g respectively B And h I The nth element of (1).
4) The goal of the optimization is to maximize the effective throughput of the communication system, from which the following optimization problem can be constructed:
the constraints are a concealment constraint, a maximum transmit power constraint and a maximum codeword length constraint, respectively. Since the relative sizes of the concealment constraints and the prior probabilities are closely related, the next step is to divide the cases to maximize the effective throughput of the system.
Thirdly, solving the optimization problem through scene-by-scene discussion:
the optimization problem (11) is decomposed into two sub-optimization problems by classifying the magnitude relation of the prior probabilities.
Scenario 1: rho 0 ＞ρ 1
At this time, substituting (11) the specific expressions of the prior probability and the information transmission rate to obtain a first sub-optimization problem as follows:
it can be readily seen that η is monotonically increasing with respect to L, and in addition, η is monotonically increasing with respect to γ b The first derivative of (a) is as follows:
when the signal-to-interference-and-noise ratio y of the received signal at Bob b When greater than 1, then there are
Since the Q inverse function monotonically decreases with respect to the bit error rate delta, as long as delta > 2.66X 10 is ensured -4 Can be got to->
At this time, η is about γ b Is greater than 0, the optimization objective function is with respect to gamma b Is monotonically increasing. Simultaneous gamma b In respect of P a Is also monotonically increasing, so η is obtained with respect to P a Monotonically increasing. Since the objective function is with respect to P a And L are both monotonically increasing, so the optimum transmit power is taken to be the maximum value within its value range no matter what value L takes. Therefore, the optimal transmitting power can be obtained first, and the optimal transmission code word length is solved on the basis. The optimal transmit power and optimal transmit codeword length given scenario 1 are as follows:
wherein
Is satisfied with>
Is preferably the maximum value within the range of (a).
Scenario 2: rho 0 ≤ρ 1
And (11) substituting specific expressions of the prior probability and the information transmission rate into the formula (11) to obtain a second sub-optimization problem as follows:
similar to the analysis method of scenario 1, a transmit power P for Alice can be solved through the concealment constraint a According to the maximum power constraint, obtaining the constraint conditions of P a The preliminary optimal solution of (a) is as follows:
and then bringing the initial optimal solution into an objective function, classifying and discussing again, and analyzing monotonicity of the objective function about L so as to obtain the optimal solution of L. The optimal transmit power and optimal transmit codeword length given scenario 2 are as follows:
wherein
Is satisfied with>
Is greater than or equal to>
L p Is to be
After the objective function is substituted, zero point of the first derivative of L is satisfied, and Bln 2/lambda is less than or equal to L p ≤L max 。
The optimal solutions obtained in scenario 1 and scenario 2 are brought into the expression (2) of the prior transmission probability, and the optimal prior transmission probability for maximizing the effective throughput can be obtained.
The invention has the beneficial effects that:
the invention solves the optimal power detection threshold of the eavesdropper under unequal prior probability to realize the optimal detection, and under the condition of the least disadvantage to both sides of legal communication and under the limitation condition of covert communication, the optimal transmitting power, the optimal code word length and the optimal prior transmission probability of the intelligent reflector assisted covert communication are given, which indicates that the optimal prior transmission probability for realizing the maximum effective throughput is not necessarily 0.5. The invention provides a reference value method for how to arrange the intelligent reflecting surface and how to set the optimal code word length and the optimal transmitting power.
Drawings
FIG. 1 is a diagram of an unequal prior probability covert communication system based on an intelligent reflecting surface.
Fig. 2 is a graph showing the influence of the power detection threshold value and the transmission power of an eavesdropper on the average detection error probability thereof when they are varied.
Fig. 3 is a graph of the effect on the optimal transmitted codeword length when the maximum codeword length and the tolerance value vary.
Fig. 4 is a graph of the impact on optimal transmit power and maximized effective throughput for variations in maximum codeword length and tolerance values.
Fig. 5 is a graph of the effect of maximum codeword length and decoding average error probability on maximizing goodput.
Fig. 6 is a graph of the effect on the optimal transmit codeword length and the optimal transmit power when the poisson rate and the maximum transmit power vary.
Fig. 7 is a graph of the impact on maximum effective throughput and optimal a priori transmission probability as poisson rate and maximum transmit power vary.
Detailed Description
In order to better understand the technical solution, specific analysis is given below with reference to the accompanying drawings and specific embodiments.
A hidden communication method under the condition of unequal prior probability by using the assistance of an intelligent reflecting surface comprises the steps of firstly optimizing a phase shift matrix of the intelligent reflecting surface to enable the signal-to-interference-and-noise ratio at a legal receiving end to be maximum, and then jointly optimizing the transmitting power P of a transmitting end a And the transmission codeword length L achieves covert communication that prevents interception by eavesdroppers with optimal detection, and achieves maximum goodput while ensuring concealment. The method comprises the following specific steps:
in the first step, the following settings are made:
1) The positions of the transmitting end Alice, the legal receiving end Bob, the eavesdropper Willie and the intelligent reflecting surface are fixed, namely Alice (0, 0), bob (180, 10, 0), willie (-300, 0) and the intelligent reflecting surface (180, 0, 30).
2) The number of the reflecting elements of the intelligent reflecting surface, the system bandwidth and the decoding error probability are set as follows: m =36, B =15kHz, δ =0dBm. The channel rayleigh fading, large-scale fading parameters and rayleigh fading parameters are as follows: beta is a beta 0 ＝-20dBdB、α＝4.4、β ab ＝β aw And =1. The noise power is set as:
second, the best detection of the eavesdropper Willie was analyzed:
fig. 2 analyzes the effect of different power detection thresholds and transmit powers on Willie's average detection error probability. It can be seen from the figure that, as the power detection threshold increases, the average detection error probability continuously decreases from a stable value to a lowest point, and continuously increases to another stable point, which indicates that Willie has an optimal detection threshold so that the detection accuracy reaches the highest; and the lowest average detection error probability decreases with increasing transmit power, since an increase in transmit power will cause an increase in relative entropy, which is more beneficial to an eavesdropper, so Alice's transmit power needs to be carefully chosen.
Thirdly, the influence of different parameters on the optimal solution is respectively analyzed:
fig. 3 illustrates the effect of different tolerance values and different maximum transmission codeword lengths on the optimal transmission codeword length. Five sets of tolerance values were compared in the experiment, and it can be seen from the data in the figure that the tolerance values have no effect on the optimal transmitted codeword length because the tolerance values in the concealment constraint do not contribute to the optimal transmitted codeword length. Secondly, as the maximum transmission codeword length increases, the optimal transmission codeword length remains constant after first increasing, which is inconsistent with the conclusion that the optimal transmission codeword length obtained from most of the prior probabilities is the maximum transmission codeword length. Since the optimal a priori transmission probability increases monotonically with the optimal transmission codeword length, it also means that the optimal a priori probability is not necessarily 0.5 at all times.
Fig. 4 illustrates the effect of different tolerance values and different maximum transmission codeword lengths on the optimal transmit power and maximum effective throughput. As can be seen from the figure, as the maximum codeword length increases, the optimal transmission power also increases and then remains stable, and the increase in transmission power increases the throughput and also increases the risk of being detected by an eavesdropper, so a balance needs to be finally maintained. In addition, as the tolerance value increases, the optimal transmit power will also increase continuously until a stable value, because as the tolerance value increases, the concealment constraint becomes less stringent and more room is provided for the transmit power to vary.
Fig. 5 illustrates the effect of maximum codeword length and decoding average error probability on maximum goodput given a tolerance value. As the average probability of error in decoding increases, the maximum goodput also increases because the increase in average probability of error in decoding increases the rate of information transfer between legitimate correspondents, thereby affecting goodput.
Fig. 6 and fig. 7 analyze the influence of the poisson rate and the maximum transmission power on the optimal transmission codeword length, the optimal transmission power, the maximum effective throughput and the optimal a priori transmission probability, respectively. As the maximum transmit power increases, the optimum transmit power increases first and then remains stable because when the maximum transmit power reaches a certain level, the privacy constraint will act to limit the value of the transmit power. Since the goodput is affected by the sir and the transmit power at Bob at the same time, and the parameters that play the leading role at different times are different, the maximum goodput will have a trend of increasing first and then decreasing. When the poisson rate is small, only the constraint of the maximum transmission code word length acts, even if the optimal transmission code word length reaches the maximum value, because the optimal prior transmission probability is small, when the optimal transmission power is small, the maximum effective throughput obtained by the rate is lower than the maximum effective throughput under other rates.
The above-mentioned embodiments only express the embodiments of the present invention, but not should be understood as the limitation of the scope of the invention patent, it should be noted that, for those skilled in the art, many variations and modifications can be made without departing from the concept of the present invention, and these all fall into the protection scope of the present invention.
Claims (3)
1.A covert communication method based on an intelligent reflecting surface under unequal prior probability is characterized by comprising the following steps:
firstly, constructing a system model:
1) The transmitting end (Alice) and the legal receiving end (Bob) are carrying out legal communication, and the communication fact is expected not to be detected by an eavesdropper (Willie); by arranging the intelligent reflecting surface with M reflecting elements, signals received by Bob and Willie are formed by superposing signals transmitted by a direct ground link and signals transmitted by a reflecting link of the intelligent reflecting surface;
2) The communication channel between Alice and Bob and the eavesdropping channel between Alice and Willie are both a superposition of large-scale fading and Rayleigh fading distributions
Wherein beta is 0 ，α，h e Respectively representing the power gain at each 1m reference distance, the large-scale fading factor and the random distribution parameter of the Rayleigh channel, wherein h e Obedience mean 0, variance β e Complex gaussian distribution of e = ab, aw, d k K ∈ { ab, aw } represents the distance between nodes;
the channel from Alice to the intelligent reflecting surface is the superposition of large-scale fading and Rayleigh fading distribution
The channels from the intelligent transmitting surface to Bob and Willie are also the superposition of large-scale fading and Rayleigh fading profiles->
Wherein h is I And g m M = B, W are M × 1 and 1 × M matrices characterizing rayleigh fading, respectively, d j K belongs to { ai, ib, iw } and represents the distance between the intelligent reflecting surface and the ground node; considering additive white Gaussian noise, and->
Noise power at Willie and Bob respectively; alice sends Gaussian information sequence x [ i],i＝1,2,...,L；
3) Transmitting power P of transmitting terminal Alice a Not exceeding the upper power limit P max The length L of the transmitted code word does not exceed the upper limit L of the code word length max ；
4) Let R denote the information transfer rate between Alice and Bob:
wherein, γ b Is the signal to interference and noise ratio at Bob,
called the Q function, also called the right tail function of the standard normal distribution, Q -1 (x) Is the inverse of the Q function, δ represents the average error probability of decoding at Bob;
5) The prior probability of Alice at each transmission cycle can be given by modeling the arrival of a packet at this event as a poisson process with a rate λ:
ρ 1 ＝1-e -λT (2)
ρ 0 ＝1-ρ 1 ＝e -λT (3)
wherein ρ 1 Means the probability, ρ, that Alice chooses to transmit a signal 0 Representing the probability that Alice chooses to remain silent;
on the premise of a given rate lambda, the prior transmission probability is only determined by the packet transmission duration T; for packet transmission duration T, the bandwidth of the transmission system is B, which is rewritten as:
6) Given that the average error probability of decoding at the receiving end cannot be neglected in communications with limited transmitted codeword lengths, given the goodput η from the transmitting end to the legitimate receiving end based on (1):
η＝ρ 1 R(1-δ) (5)
step two, listing an optimization problem according to the system model:
1) To determine whether legitimate communication behavior exists, willie's binary hypothesis test is as follows:
willie wants to adopt the best detection scheme to minimize the average false detection probability of Willie; according to the criterion of maximum likelihood
Solving an optimal power detection threshold gamma * (ii) a Willie compares the received signal power, as measured by the power detector radiometer, with Γ * To judge the communication condition between Alice and Bob; when the power of the received signal is larger than a preset detection threshold, judging that the communication behavior occurs, otherwise, judging that the communication behavior does not occur;
2) In order to ensure the implementation of covert communication, a restrictive condition of covert communication needs to be given:
wherein ε is the tolerance value; by further scaling the relative entropy, a final concealment constraint expression is obtained,
3) For any given transmit power P a And transmission codeword length L, optimal
The goal of (a) is always to maximize the received signal strength at Bob; i.e. require +>
The die length of (a) is maximized due to h ab Is a complex scalar, has a phase angle, and>
is also a complex scalar quantity, provided that g B Θh I And h ab Is the same, so that->
The die length of (a) is maximized; therefore, the best phase can be obtained:
θ n ＝arg(h ab )-arg(g B ,n)-arg(h I ,n) (10)
where arg (a) is the phase angle of a complex scalar a, g B N and h I N represents g respectively B And h I The nth element of (1);
4) The goal of the optimization is to maximize the effective throughput of the communication system, and the following optimization problem is constructed from the model:
0<P a ≤P max
0<L≤L max
and thirdly, solving an optimization problem.
2. The covert communication method based on the unequal prior probability of the intelligent reflecting surface as claimed in claim 1, wherein the third step of solving the optimization problem specifically comprises the following operations:
by classifying the magnitude relationship of the prior probabilities, scenario 1: ρ is a unit of a gradient 0 ＞ρ 1
Substituting (11) the specific expressions of the prior probability and the information transmission rate to obtain an optimization problem as follows:
0<P a ≤P max
eta is monotonically increasing with respect to L, and, moreover, eta is monotonically increasing with respect to gamma b The first derivative of (a) is as follows:
when the signal-to-interference-and-noise ratio y of the received signal at Bob b When greater than 1, there are
Since the Q inverse function decreases monotonically with respect to the bit error rate, δ, as long as δ > 2.66 × 10 is ensured -4 Can be got to->
At this time, η is about γ b Is greater than 0, the optimization objective function is with respect to gamma b Is monotonically increasing; simultaneous gamma b In respect of P a Is also monotonically increasingSo that η is obtained with respect to P a Monotonically increasing; since the objective function is with respect to P a And L are monotonically increasing, so that no matter what value L takes, the optimal transmitting power is the maximum value in the value range; so that the optimum transmitting power can be obtained first,
then, on the basis, the optimal transmission code word length is solved; the optimal transmit power and optimal transmit codeword length given scenario 1 are as follows:
wherein the content of the first and second substances,
is satisfied with>
Maximum value within the desirable range of (a);
and (3) bringing the obtained optimal solution into an expression (2) of prior transmission probability to obtain the optimal prior transmission probability for realizing the maximization of effective throughput.
3. The covert communication method based on the unequal prior probability of the intelligent reflecting surface as claimed in claim 1 or 2, wherein the third step is to solve the optimization problem, and the specific operations are as follows:
by classifying the magnitude relationship of the prior probabilities, scenario 2: rho 0 ≤ρ 1
Substituting (11) the specific expressions of the prior probability and the information transmission rate to obtain an optimization problem as follows:
0<P a ≤P max
Bln2/λ≤L≤L max
solving a transmitting power P related to Alice through a concealment constraint a According to the maximum power constraint, obtaining the constraint condition about P a The initial optimal solution of (a) is as follows:
then bringing the initial optimal solution into a target function, classifying and discussing again, and analyzing monotonicity of the target function about L so as to obtain the optimal solution of L; the optimal transmit power and optimal transmit codeword length given scenario 2 are as follows:
wherein
Is satisfied with>
The maximum value of (a) is,
L p is to be
After the objective function is substituted, zero point of the first derivative of L is satisfied, and Bln 2/lambda is less than or equal to L p ≤L max ；
And (3) bringing the obtained optimal solution into an expression (2) of prior transmission probability to obtain the optimal prior transmission probability for realizing the maximization of effective throughput.
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Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN117042162A (en) * | 2023-10-09 | 2023-11-10 | 中国移动紫金(江苏)创新研究院有限公司 | Communication method, device, reflection plane, computing system, enhancer and repeater |
| CN117241361A (en) * | 2023-11-13 | 2023-12-15 | 北京航空航天大学 | Short wave hidden communication method based on power control |
| CN117835230A (en) * | 2023-12-29 | 2024-04-05 | 三峡大学 | Probability hidden transmission method based on link information |
| CN118054977A (en) * | 2024-04-16 | 2024-05-17 | 昆明学院 | Hybrid mode-based joint concealment and secure communication system and method |
| CN117835230B (en) * | 2023-12-29 | 2024-07-05 | 三峡大学 | Probability hidden transmission method based on link information |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117042162A (en) * | 2023-10-09 | 2023-11-10 | 中国移动紫金(江苏)创新研究院有限公司 | Communication method, device, reflection plane, computing system, enhancer and repeater |
| CN117042162B (en) * | 2023-10-09 | 2023-12-26 | 中国移动紫金(江苏)创新研究院有限公司 | Communication method, device, reflection plane, computing system, enhancer and repeater |
| CN117241361A (en) * | 2023-11-13 | 2023-12-15 | 北京航空航天大学 | Short wave hidden communication method based on power control |
| CN117241361B (en) * | 2023-11-13 | 2024-02-06 | 北京航空航天大学 | Short wave hidden communication method based on power control |
| CN117835230A (en) * | 2023-12-29 | 2024-04-05 | 三峡大学 | Probability hidden transmission method based on link information |
| CN117835230B (en) * | 2023-12-29 | 2024-07-05 | 三峡大学 | Probability hidden transmission method based on link information |
| CN118054977A (en) * | 2024-04-16 | 2024-05-17 | 昆明学院 | Hybrid mode-based joint concealment and secure communication system and method |
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