A Covert Energy-Aware Routing Method in a Multi-Listener and Multi-Confidential User Scenario

Abstract

The present invention discloses a covert energy-efficient routing method in a scenario of multiple eavesdroppers and multiple secure users, which includes establishing an energy-efficient integrated network diagram in a scenario of joint eavesdropping by multiple eavesdroppers; obtaining the network transmission requirements and the energy states of secure user nodes in the control phase; generating a transmission matrix for all data streams according to the network transmission requirements; constructing an optimization model for maximizing the total covert uplink throughput data volume of users, and solving to obtain the routing path selection result and the time slot resources allocated to the routing path; in the transmission phase, transmitting the data streams according to the selected routing paths and the allocated time slot resources, and enabling the secure user nodes to perform covert transmission with the assistance of the corresponding data streams. The present invention provides an energy replenishment service for user nodes on the basis of meeting the original data stream transmission requirements of the routing layer, improves the practicability and application scope of the covert energy-efficient joint routing method, and effectively improves the covert communication performance of the network.

Description

Technical Field

[0001] The present invention relates to the technical field of covert data-energy routing, and particularly relates to a covert data-energy routing method in a scenario with multiple eavesdroppers and multiple secure users. Background Art

[0002] With the development of the Internet of Things (IoT) technology, a large number of IoT devices are connected to the network, and ensuring the sustainable energy supply of the devices has become a challenge. Data and energy integrated networks (DEIN) can achieve wireless integrated transmission of data and energy, and can provide energy replenishment services for IoT devices while communicating with them. Due to the broadcast nature of the wireless channel, devices around the transmission node can also obtain a certain amount of energy through energy harvesting. Therefore, the routing algorithm in the data-energy integrated network not only affects the communication performance of the network, but also directly relates to the energy replenishment effect of IoT devices around the path.

[0003] The broadcast nature of the wireless channel also causes wireless communication to be easily intercepted or disrupted by eavesdroppers. Covert communication related technologies can transmit data without being detected by eavesdroppers, which can fundamentally avoid information leakage. However, the performance of covert communication is subject to the square root law, and it is necessary to increase the uncertainty of the eavesdropper's understanding of the communication system to improve the covert data throughput; and in the actual scenario, the eavesdropping party often deploys multiple eavesdroppers to cooperate in eavesdropping, and the number of nodes that require secure communication is often more than one, which limits the generality of conventional covert data-energy joint routing algorithms. Using the data stream transmitted in the data-energy integrated network to interfere with the eavesdropper is a feasible solution. Studying the covert communication mechanism in the data-energy integrated network and further increasing the uncertainty of the data stream routing through the routing algorithm can improve the covert communication performance of users in the network. Summary of the Invention

[0004] In view of the above deficiencies in the prior art, the present invention provides a covert data-energy routing method in a scenario with multiple eavesdroppers and multiple secure users.

[0005] To achieve the above invention purpose, the technical solution adopted by the present invention is as follows:

[0006] A covert data-energy routing method in a scenario with multiple eavesdroppers and multiple secure users, comprising the following steps:

[0007] S1. Establish a data-energy integrated network diagram in a scenario of joint eavesdropping by multiple eavesdroppers, and set a corresponding routing superframe; the routing superframe includes a control phase and a transmission phase;

[0008] S2. Obtain the network transmission requirements and the energy status of the secure user nodes in the control phase;

[0009] S3. Generate the transmission matrix for all data flows according to the network transmission requirements;

[0010] S4. Construct an optimization model for maximizing the total covert uplink throughput data volume of users based on the transmission matrix of the data flow and the energy state of the secure user nodes, and solve to obtain the routing path selection result and the time slot resources allocated to the routing path;

[0011] S5. During the transmission phase, transmit the data flow according to the selected routing path and the allocated time slot resources, and enable the secure user nodes to perform covert transmission with the assistance of the corresponding data flow.

[0012] Optionally, the integrated digital and energy network in the multi-eavesdropper joint listening scenario established in step S1 specifically includes:

[0013] Establish an integrated digital and energy network diagram including multiple wireless integrated digital and energy transmission routing nodes, multiple secure user nodes with energy harvesting functions, and multiple eavesdropper nodes;

[0014] Among them, the wireless integrated digital and energy transmission routing nodes form the routing layer of the integrated digital and energy network, which is used to provide data energy routing services for all users in the integrated digital and energy network, provide energy replenishment services for all user nodes, and interfere with all eavesdropper nodes to achieve covert communication of user nodes;

[0015] The secure user nodes are equipped with supercapacitors that can store energy, forming the user layer of the integrated digital and energy network, which is used to collect environmental information and upload it to the routing layer without being discovered by eavesdroppers, and harvest the energy in the digital and energy signal through energy harvesting;

[0016] The eavesdropper nodes are used to judge whether each secure user node is communicating through joint listening.

[0017] Optionally, setting the corresponding routing superframe in step S1 specifically includes:

[0018] During the control phase, create a superframe, synchronize the network, summarize the transmission requirements, generate routing paths and allocate transmission resources, and allocate interference data flows to the user transmission requirements;

[0019] During the transmission phase, evenly divide the data flow into multiple time periods with a set duration, and each time period is further evenly divided into multiple time slots, and each time slot is allocated to the transmission matrix of the data flow generated during the control phase.

[0020] Optionally, step S3 specifically includes:

[0021] S31. Obtain the data flow of the routing layer and the hop count limit threshold of the routing path, and initialize the transmission matrix as a non-empty set;

[0022] S32. Generate a set of paths where the data flow goes from the starting point to the ending point and the routing hop count is below the routing path hop count limit threshold using the breadth - first search algorithm;

[0023] S33. Map the set of paths as feasible routing paths into a column vector;

[0024] S34. Update the union of the column vector and the transmission matrix to a new transmission matrix.

[0025] Optionally, in step S4, constructing an optimization model for maximizing the total covert uplink throughput data volume of users based on the transmission matrix of the data flow and the energy state of the secure user nodes specifically includes:

[0026]

[0027] s.t.

[0028]

[0029]

[0030]

[0031]

[0032]

[0033]

[0034]

[0035]

[0036] where, Λ S is the total covert uplink throughput data volume of users, T k is the k - th time period into which the data flow is divided, B is the user allocation matrix, |F| is the number of time periods, K S is the number of secure user nodes, is the covert uplink throughput data volume of user s j in time period T k , is a 0 - 1 variable indicating whether user s j will perform uplink transmission during data flow transmission, N S is the set of secure user nodes, is the energy harvested by user s j during transmission in time period T k , is if user s j in time period T kThe energy consumed during communication, E other The energy consumption of the user other than communication For the eavesdropper node w m To eavesdrop on any secure user node s j The eavesdropping error rate, ρ W The threshold of the covert transmission error rate, N W The set of eavesdropper nodes, M k The number of time slots for time period division For the time period T k The time slot divided by the time period T, T tra The total duration of the transmission phase The path channel capacity of the i-th path corresponding to the k-th data stream in the transmission matrix, D k The data volume requirement for transmitting the k-th data stream

[0037] Optionally, the obtained routing path selection result and the time slot resources allocated to the routing path in step S4 specifically include:

[0038] Solving the maximum covert uplink throughput data volume of the data stream assisting a single user according to all secure user nodes and data streams;

[0039] Constructing a bipartite graph based on the maximum covert uplink throughput data volume of the data stream assisting a single user, and using the KM algorithm to obtain the maximum matching to generate an optimal user allocation matrix;

[0040] Substituting the optimal user allocation matrix into the optimization model for maximizing the total covert uplink throughput data volume of the user, and solving to obtain the local optimal time slot allocation and the total maximum covert uplink throughput data volume.

[0041] Optionally, the specific process of solving the maximum covert uplink throughput data volume of the data stream assisting a single user according to all secure user nodes and data streams includes:

[0042] When not considering the energy requirement, constructing an optimization model for maximizing the covert uplink throughput data volume of the data stream assisting a single user according to all secure user nodes and data streams, which is expressed as:

[0043]

[0044] s.t.

[0045]

[0046]

[0047]

[0048]

[0049] Among them, is the transmission power of the confidential user node, is the wireless data and energy integrated transmission routing node r l and the confidential user node s j the channel gain between them, represents whether the routing node r m is activated to transmit data in time slot t i , is the transmission power of the routing node r m , is the routing node r l and the routing node r m the channel gain between them, is the signal power expectation of the wireless data and energy integrated transmission routing node r m , is the eavesdropper node w n for the confidential user node s j the optimal threshold for eavesdropping, is the eavesdropper node w n the noise of, is the wireless data and energy integrated transmission routing node r m the signal power variance of, is an intermediate variable, is the confidential user node s j and the eavesdropper node w n the channel gain between them.

[0050] Optionally, the construction of the bipartite graph according to the maximum covert uplink throughput data volume of all data streams assisting a single user specifically includes:

[0051] Taking the data stream and the confidential user node as the point sets on both sides of the bipartite graph, and taking the set composed of the maximum covert uplink throughput data volume of the confidential user node under the assistance of the data stream as the edge set between the point sets on both sides of the bipartite graph.

[0052] The present invention has the following beneficial effects:

[0053] The present invention obtains the optimal allocation relationship matrix for the covert communication of users assisted by data streams through a heuristic algorithm, jointly optimizes the routing selection and time slot allocation to maximize the total uplink covert communication throughput of users, provides an energy supply service for user nodes on the basis of meeting the original data stream transmission requirements of the routing layer, improves the practicability and application scope of the covert data and energy joint routing method, and effectively improves the covert communication performance of the network. Description of the Drawings

[0054] Figure 1Schematic flowchart of a covert energy-efficient routing method in a multi-listener multi-secret user scenario in an embodiment of the present invention;

[0055] Figure 2 Schematic diagram of an energy-harvesting integrated network in a multi-eavesdropper joint eavesdropping scenario in an embodiment of the present invention;

[0056] Figure 3 Schematic diagram of a covert energy-efficient joint routing superframe in an embodiment of the present invention. Detailed implementation manners

[0057] The following describes the detailed implementation manners of the present invention to facilitate those skilled in the art of the present technology to understand the present invention. However, it should be clear that the present invention is not limited to the scope of the detailed implementation manners. For those of ordinary skill in the art of the present technology, as long as various changes are within the spirit and scope of the present invention defined and determined by the appended claims, these changes are obvious, and all inventions and creations using the concept of the present invention are within the scope of protection.

[0058] As Figure 1 shown, an embodiment of the present invention provides a covert energy-efficient routing method in a multi-listener multi-secret user scenario, including the following steps S1 to S5:

[0059] S1. Establish an energy-harvesting integrated network diagram in a multi-eavesdropper joint eavesdropping scenario and set a corresponding routing superframe; the routing superframe includes a control phase and a transmission phase;

[0060] In an optional embodiment of the present invention, the energy-harvesting integrated network established in step S1 in the multi-eavesdropper joint eavesdropping scenario specifically includes:

[0061] Establish an energy-harvesting integrated network diagram including multiple wireless energy-harvesting integrated transmission routing nodes, multiple secure user nodes with energy harvesting functions, and multiple eavesdropper nodes;

[0062] Among them, the wireless energy-harvesting integrated transmission routing nodes form the routing layer of the energy-harvesting integrated network, which is used to provide data energy routing services for all users in the energy-harvesting integrated network, provide energy supply services for all user nodes, and interfere with all eavesdropper nodes to achieve covert communication of user nodes;

[0063] The secure user nodes are equipped with supercapacitors that can store energy, form the user layer of the energy-harvesting integrated network, are used to collect environmental information, and upload it to the routing layer without being discovered by eavesdroppers, and harvest the energy in the energy-harvesting signal through energy harvesting;

[0064] The eavesdropper nodes are used to judge whether each secure user node is communicating through joint eavesdropping.

[0065] Specifically, setting the corresponding routing superframe in step S1 includes:

[0066] In the control phase, superframe creation, network synchronization, aggregation of transmission requirements, generation of routing paths, allocation of transmission resources, and assignment of interfering data streams to user transmission requirements are performed;

[0067] In the transmission phase, the data stream is evenly divided into multiple time periods of a set duration, each time period is further evenly divided into multiple time slots, and each time slot is assigned to the transmission matrix of the data stream generated in the control phase.

[0068] Specifically, as Figure 2 shown, it is an energy and data integrated network with multiple eavesdroppers and multiple secure user nodes. There are three types of nodes in this system: namely, K R wireless energy and data integrated transmission routing nodes N R ={r m |m = 1,...K R}, K S secure user nodes N with energy harvesting function S ={s j |j = 1,...K S} and K W eavesdropper nodes N W ={w n |n = 1,...K W}. The routing nodes N R constitute the routing layer in the energy and data integrated network, and their functions include: 1) providing data energy routing services for all users in the network; 2) providing energy replenishment services for all user nodes N S ; 3) interfering with all eavesdropper nodes N W to achieve covert communication of user nodes. The user nodes N S are equipped with supercapacitors that can store a certain amount of energy and constitute the user layer in the energy and data integrated network. Their functions include: 1) collecting key information in the environment and uploading it to the routing layer without being detected by eavesdroppers; 2) harvesting energy from the energy and data signal through energy harvesting to maintain user survival and corresponding functions. The main function of the eavesdropper nodes N W is to jointly eavesdrop to determine whether each user node is communicating.

[0069] The energy and data integrated network model is represented by G(N, L), where N = N R ∪N S , and L = L R ∪L S . The data transmission requirements in the network are represented by the data stream set F.

[0070] As Figure 3As shown in the figure, it is a schematic diagram of a routing superframe in the case of multiple listeners. The routing superframe is divided into two phases: the control phase T ctr and the transmission phase T tra . In addition to the functions of creating a superframe, network synchronization, summarizing transmission requirements, generating a routing path, and allocating transmission resources that are consistent with those in Chapter 3, the function of the control phase T ctr also includes allocating interference data streams to user transmission requirements to achieve the effect of covert communication. The transmission phase T tra is evenly divided into time periods of length T tra / |F| according to the data stream F, {T k |k = 1,..., |F|}|. The time period T k can be further divided into M k time slots and allocated to the generated transmission matrix representing the routing path. For the routing layer, its transmission requirements are allocated to the corresponding time periods in units of data streams, and transmission is carried out according to the paths and time slot resources allocated by the routing algorithm in the T ctr phase. For the user layer, the user nodes N S are allocated different data streams f k in units of nodes to assist in uplink covert communication in the corresponding time periods, and energy is harvested in the remaining time periods to obtain the energy to maintain the survival of the user nodes. In order for the routing layer to provide sufficient energy to the users, the number of data streams is set to be greater than the number of users in this chapter. Therefore, not every data stream will be used to interfere with the listeners during the uplink covert communication of the users.

[0071] S2. Obtain the network transmission requirements in the control phase and the energy status of the secure user nodes;

[0072] S3. Generate the transmission matrix of all data streams according to the network transmission requirements;

[0073] In an alternative embodiment of the present invention, this embodiment uses |F| transmission matrices A R with dimensions of K k ×M k to represent the activation status of the routing nodes corresponding to the feasible transmission paths of the data stream f k , where 1 or 0 indicates whether the routing node r m is activated to transmit data in the time slot corresponding to .

[0074] The method of generating the transmission matrix of all data streams according to the network transmission requirements specifically includes:

[0075] S31. Obtain the data stream f k of the routing layer and the hop count limit threshold N hop of the routing path, and initialize the transmission matrix as a non-empty set

[0076] S32. Generate the data stream f using the breadth - first search algorithm k The path set Ω from the starting point to the ending point and with the number of routing hops within the routing path hop - count limit threshold N hop ; k ;

[0077] S33. Map the path set Ω k as the feasible routing path into a column vector

[0078] S34. Update the union of the column vector and the transmission matrix as the new transmission matrix

[0079] S4. Construct an optimization model for maximizing the total covert uplink throughput data volume of users according to the transmission matrix of the data stream and the energy state of the secure user nodes, and solve to obtain the routing path selection result and the time - slot resources allocated to the routing path;

[0080] In an alternative embodiment of the present invention, for the secure user nodes, a user allocation matrix B with dimensions K S ×|F| is used to represent the activation of the secure user nodes in different data streams. Specifically, is 0 or 1, indicating whether s j will perform uplink transmission when the data stream f k is transmitted. At the same time, according to the characteristics of the digital - energy integrated network model, for the user allocation matrix B, there are corresponding constraint conditions:

[0081]

[0082]

[0083]

[0084] Among them, constraint (1) means that the user allocation matrix B is only composed of 0 or 1, constraint (2) means that at most one secure user node is assisted for uplink covert communication when the same data stream f k is transmitted, and constraint (3) means that each secure user node needs to perform an uplink covert communication once in a round of super - frames.

[0085] Regarding the energy performance of the set N S of secure user nodes, since there is no stable sequence relationship between the transmission of users and the data stream at the routing layer, it is necessary to additionally consider the energy causality of the user nodes. The energy constraint of the user node s j is as follows:

[0086]

[0087] Among them, denotes s j the remaining energy before the start of each superframe in the network, denotes s j the energy harvested through energy harvesting during transmission in time period T p E other denotes the energy consumption of the user other than communication, denotes that if s j in time period T k the energy consumed by communication. The meaning of constraint (4) is that at any time period, the remaining energy of the node is not less than 0. and Specifically expressed as:

[0088]

[0089]

[0090] Among them, β represents the energy harvesting coefficient, denotes node r m , s j the channel gain between. Considering the characteristics of the digital-energy integrated network model and routing transmission, the communication in each superframe will affect the initial energy of the next round, and the network continuously cycles and transmits on a larger time scale. Considering as a whole, if the appropriate initial energy is set and it is ensured that the energy obtained by node s j in each superframe is greater than the consumed energy, in this way, on the premise of avoiding violating the energy causality condition, the energy resources of transmitting data streams in the routing layer can be utilized more effectively, and it is also more in line with the actual usage scenario. The energy constraint at this time can be simplified as:

[0091]

[0092] According to the above analysis, by reasonably setting the causality of the system energy can be guaranteed when satisfied.

[0093] For the uplink throughput of the user node, the secure user node s j will select the nearest routing node r i to transmit data, and the uplink throughput data volume of the secure user node s j in time slot T k can be obtained as:

[0094]

[0095] All eavesdroppers N in the network W will be in the digital-energy integrated network transmission stage T traPerform joint listening on all user nodes N S to determine whether there is communication. Since the eavesdropper is constantly listening in the network, it is assumed that all eavesdroppers know the statistical parameters such as the activation probability and channel gain of all nodes in the number-energy integrated network. However, at a specific moment, the eavesdropper cannot know which specific nodes are in the active state. At the same time, the eavesdropper will use the joint listening strategy, and any eavesdropper w n judges whether user s j has communication. If it is determined that there is communication, it can be considered that there is communication. Accordingly, the decision formula for the eavesdropper w n to determine whether there is communication for s k during period T j can be expressed as:

[0096]

[0097] where, is the average received signal power of the eavesdropper during period T k , is the single received signal of the eavesdropper w n during period T k , N is the number of listening times of the eavesdropper during T k , D1 and D0 represent the decision of the eavesdropper w n on whether there is covert communication for the user node s j in the network, is the decision threshold. Through analysis, it can be obtained that the more the number of listening times N , the more accurate, and the better the listening effect of the eavesdropper. Therefore, in this embodiment, N→∞ is designed to improve the listening ability of the eavesdropper, so that the covert number-energy joint routing method can still achieve good results in the face of more adverse scenarios. According to Equation (9), the binary hypothesis of the received power of w n during period T k can be deduced as:

[0098]

[0099]

[0100] where, represents the noise of the eavesdropper w n , represents the null hypothesis: that is, w n judges that s j does not transmit data during period T k ; represents the alternative hypothesis: w n judges that s j has data communication at time T k . Since the eavesdropper can only infer the activation probability of all nodes from historical data without knowing T k the specific routing and node activation conditions during the time period, so in w n From the perspective of the eavesdropper, the received power part of the routing nodes in equations (10) and (11) cannot be accurately obtained. Therefore, from the perspective of the eavesdropper, the statistical information of the network can be used to make a reasonable assumption about the activation situation of the routing nodes. The power expectation and variance of the received r i signal are:

[0101]

[0102]

[0103] According to the Lyapunov central limit theorem, let the binary hypotheses (10) and (11) from the perspective of the eavesdropper can be rewritten as:

[0104]

[0105]

[0106] It should be noted that due to constraints (2) and (3), the activation of the user nodes is not independent, so the Lyapunov central limit theorem cannot be applied. Based on the above analysis, in this embodiment, the false alarm probability of the eavesdropper and the miss detection probability can be comprehensively analyzed to obtain the optimal decision threshold false alarm rate and miss detection rate The formulas are as follows:

[0107]

[0108]

[0109] where, using to simplify the formula expression. According to the network characteristics, the transmission power of the routing nodes is much greater than the transmission power of the user nodes Therefore, without loss of generality, it can be considered that P2 > P3. At this time, when the eavesdropper listens to w n for user s j the error probability of listening is:

[0110]

[0111] where, Analyzing equation (18), it can be found that Regarding It is continuous in the interval [P1, P4), monotonically decreasing in the interval [P1, P3], and monotonically increasing in the interval [P2, P4]. Therefore, from the perspective of the listener w n the optimal case must be taken from the interval [P3, P2], and the formula is expressed as:

[0112]

[0113] where Since Equation (19) is a single-variable function with respect to it can be found within the interval through one-dimensional search and From this, the constraints of covert communication can be obtained. Because the listeners in this embodiment adopt the combined listening method, the listening error rate of any listener N W listening to any user N S must satisfy the following conditions:

[0114]

[0115] where ρ W is the threshold of the covert transmission error rate.

[0116] In this embodiment, through path selection and time slot resource allocation, using the data stream actually transmitted by the routing layer in the network, wireless energy transmission and assisted covert communication services are provided for the user layer, and on this basis, wireless data transmission services are provided. The data transmission performance of the user layer is affected by covert constraints, energy replenishment limitations, and interference from the data stream of the routing layer. Therefore, in order to ensure a balance among these constraints and improve the total uplink data volume of network users, based on the data stream transmission matrix of the routing layer, this embodiment designs an optimization model (P5-1) that maximizes the total uplink throughput of users as:

[0117]

[0118] s.t.

[0119]

[0120]

[0121]

[0122]

[0123]

[0124]

[0125] ​

[0126]

[0127] Among them, Λ S is the total hidden uplink throughput data volume of the user, T k is the k-th time period divided by the data stream, B is the user allocation matrix, |F| is the number of time periods, K S is the number of secure user nodes, is user s j in time period T k of the hidden uplink throughput data volume, is to represent user s j when the data stream is transmitted, whether it will perform uplink transmission is a 0-1 variable, N S is the set of secure user nodes, is user s j in time period T i when transmitting, the energy obtained through energy harvesting, is if user s j in time period T k when communicating, the consumed energy, E other is the energy consumption of the user other than communication, is the eavesdropping error rate of eavesdropper node w m eavesdropping on any secure user node s j of the eavesdropping error rate, ρ W is the threshold of the hidden transmission error rate, N W is the set of eavesdropper nodes, M k is the number of time slots divided by the time period, T tra is the total duration of the transmission phase, is the path channel capacity of the i-th path corresponding to the k-th data stream in the transmission matrix, D k is the data volume requirement for the transmission of the k-th data stream.

[0128] Constraints (1), (2), and (3) are the relevant constraints for the data stream to assist the user allocation matrix B. The elements in the matrix can only be integers of 0 or 1. Only one user node can be activated in the same time period, and the same user is activated in one time period during the entire transmission phase; Constraint (7) is the energy constraint at the user layer, and it is necessary to provide energy for the user nodes to meet their survival and communication through path selection and time slot allocation; Constraint (20) is the hidden communication constraint, and it is necessary to use the real data stream of the network to interfere with the eavesdropper to meet the hidden communication conditions; Constraints (21a) and (21b) are the constraints for allocating time slots in the transmission phase; (21c) is the constraint on the transmission data volume of each real data stream in the routing layer. It is necessary to improve the total uplink hidden communication throughput of the user on the basis of meeting the transmission volume of the routing layer.

[0129] The obtained routing path selection result and the time slot resources allocated to the routing path in step S4 specifically include:

[0130] Solving for the maximum covert uplink throughput data volume of a single user assisted by data streams based on all secure user nodes and data streams;

[0131] Constructing a bipartite graph based on the maximum covert uplink throughput data volume of a single user assisted by all data streams, and using the KM algorithm to obtain the maximum matching to generate an optimal user allocation matrix;

[0132] Substituting the optimal user allocation matrix into the optimization model for maximizing the total covert uplink throughput data volume of users, and solving for the local optimal time slot allocation and the total maximum covert uplink throughput data volume.

[0133] Specifically, analyzing the optimization model (P5-1) in this embodiment, it can be found that since the elements in the user allocation matrix B can only be 0 or 1, and B is highly coupled with the optimization objective (21), the energy constraint (7), and the non-convex constraint (20), the optimization problem (P5-1) is a mixed integer optimization problem. Further observing the form of the user allocation matrix B, it can be found that the original problem is a variant form of a class of allocation problems with non-convex constraints, which is an NP-hard combinatorial optimization problem. Based on the above analysis, it is difficult to obtain the optimal solution of the original problem in polynomial time. Therefore, based on the characteristics of the model and the essential characteristics of the optimization problem, this embodiment gives a heuristic solution algorithm for the optimization model (P5-1).

[0134] First, optimize the allocation matrix B. In this embodiment, the original problem is simplified to a standard allocation problem, and the optimal allocation of the standard allocation problem can be obtained through the maximum matching of a weighted bipartite graph. To achieve this goal, a bipartite graph needs to be constructed first The point sets on both sides of the bipartite graph are data streams and user nodes respectively, and the edge set between them is the set composed of the maximum uplink data volume j in the data stream f k under the assistance of the user node s. The acquisition method of

[0135]

[0136] s.t.

[0137]

[0138]

[0139]

[0140]

[0141] Among them, is the transmission power of the confidential user node, is the wireless information and energy integrated transmission routing node r l and the confidential user node s j The channel gain between them, represents whether the routing node r m is activated to transmit data in time slot t i , is the transmission power of the routing node r m , is the routing node r l and the routing node r m The channel gain between them, is the signal power expectation of the wireless information and energy integrated transmission routing node r m , is the optimal threshold for the eavesdropper node w n to eavesdrop on the confidential user node s j , is the noise of the eavesdropper node w n , is the signal power variance of the wireless information and energy integrated transmission routing node r m , is an intermediate variable, is the confidential user node s j and the eavesdropper node w n The channel gain between them.

[0142] In this embodiment, b sj,k = 1, and the covert communication constraint (20) can be rewritten as:

[0143]

[0144] The zero point of equation (23) can be solved by one-dimensional search and At this time, for different eavesdroppers w n , the constraint (23) will be transformed into:

[0145]

[0146] Substituting equation (24) back into the optimization model (P5-2), the original problem will be transformed into sub-problems, and all these sub-problems are convex optimization problems. By solving these sub-problems with the convex optimization solver CVX, the use of f k to assist a single user s jThe maximum amount of uplink covert communication data By solving the optimization model (P5-2) for all user nodes and data streams, the bipartite graph is constructed. At this time, the number of nodes on both sides of the bipartite graph does not match. Corresponding dummy nodes can be added on the user node side, and the edge weights between the dummy nodes and all data stream sides are 0. The modified bipartite graph can obtain the maximum weighted matching using the KM algorithm, and the matching scheme is the optimal allocation matrix B * .

[0147] After obtaining the optimal allocation matrix B * , then construct the optimization model (P5-3) for slot allocation in each data stream transmission stage:

[0148]

[0149] s.t.

[0150]

[0151]

[0152]

[0153]

[0154]

[0155] Since the optimal user allocation matrix B * has been obtained, the optimization objective and the constraints other than the divisor (20) are all linear constraints with respect to {T k |k = 1,..., |F|}, and the constraint (20) can be transformed into the linear constraint (23) in the same way as in the optimization model (P5-2). At the same time, during the solution process of the optimization model (P5-2), the zero points corresponding to the optimal subproblems have been obtained There is no need to select the zero points again. Therefore, the optimization model (P5-3) is a linear optimization problem, and an optimal solution can be obtained using a convex optimization solver such as CVX. At the same time, this solution is also the local optimal solution of the optimization model (P5-1).

[0156] S5. In the transmission stage, transmit the data streams according to the selected routing paths and the allocated time slot resources, and enable the secure user nodes to perform covert transmission with the assistance of the corresponding data streams.

[0157] In an alternative embodiment of the present invention, in this embodiment, the data streams are transmitted according to the selected routing paths and the allocated time slot resources {T k*Transmit for {k = 1,..., |F|}, and allocate the secure user nodes according to the optimal user allocation matrix B * Perform covert transmission with the assistance of the corresponding data stream.

[0158] Optimal user allocation matrix B * And the time slot allocation {T k* The routing selection represented by {k = 1,..., |F|} is directly related to whether the routing method can meet the constraints and requirements of data, energy, and concealment. The entire scheme changes with the superframe rounds of network communication and continuously loops to achieve the joint data and energy routing that meets the covert communication conditions in the multi-listener scenario.

[0159] The present invention is described with reference to the flowcharts and / or block diagrams of methods, apparatuses (systems), and computer program products according to embodiments of the present invention. It should be understood that each flow and / or block in the flowchart and / or block diagram, and the combination of flows and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, such that the instructions executed by the processor of the computer or other programmable data processing devices generate means for implementing the functions specified in Figure 1 one or more flows and / or blocks Figure 1 one or more blocks.

[0160] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, such that the instructions stored in the computer-readable memory generate a manufactured article including instruction means that implement the functions specified in Figure 1 one or more flows and / or blocks Figure 1 one or more blocks.

[0161] These computer program instructions can also be loaded onto a computer or other programmable data processing device, such that a series of operation steps are executed on the computer or other programmable device to generate a computer-implemented process, and thus the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in Figure 1 one or more flows and / or blocks Figure 1 one or more blocks.

[0162] In the present invention, specific embodiments are used to illustrate the principles and implementation manners of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea. At the same time, for those of ordinary skill in the art, according to the idea of the present invention, there will be changes in the specific implementation manners and application scopes. In summary, the content of this specification should not be construed as a limitation to the present invention.

[0163] Those of ordinary skill in the art will realize that the embodiments described herein are for helping the reader understand the principles of the present invention, and it should be understood that the protection scope of the present invention is not limited to such specific statements and embodiments. Those of ordinary skill in the art can make various other specific deformations and combinations that do not depart from the essence of the present invention according to these technical revelations disclosed by the present invention, and these deformations and combinations are still within the protection scope of the present invention.

Claims

1. A covert energy-efficient routing method in a multi-listener and multi-secret user scenario, characterized in that, Including the following steps: S1. Establish a digital - energy integrated network diagram under the scenario of multi - eavesdropper joint eavesdropping, and set the corresponding routing super - frame; the routing super - frame includes a control phase and a transmission phase; S2. Obtain the network transmission requirements in the control phase and the energy status of the secure user nodes; S3. Generate a transmission matrix for all data streams according to the network transmission requirements; S4. Construct an optimization model for maximizing the total covert uplink throughput data volume of users based on the transmission matrix of the data streams and the energy status of the secure user nodes, and solve to obtain the routing path selection result and the time - slot resources allocated to the routing paths; S5. In the transmission phase, transmit the data streams according to the selected routing paths and the allocated time - slot resources, and enable the secure user nodes to perform covert transmission with the assistance of the corresponding data streams.

2. The covert energy routing method in a multi - listener and multi - confidential user scenario according to claim 1, characterized in that, The digital - energy integrated network under the scenario of multi - eavesdropper joint eavesdropping established in step S1 specifically includes: Establish a digital - energy integrated network diagram including multiple wireless digital - energy integrated transmission routing nodes, multiple secure user nodes with energy harvesting functions, and multiple eavesdropper nodes; Among them, the wireless digital - energy integrated transmission routing nodes form the routing layer of the digital - energy integrated network, which is used to provide data - energy routing services for all users in the digital - energy integrated network, provide energy replenishment services for all user nodes, and interfere with all eavesdropper nodes to achieve covert communication of user nodes; The secure user nodes are equipped with supercapacitors that can store energy, forming the user layer of the digital - energy integrated network, which is used to collect environmental information and uplink it to the routing layer without being detected by eavesdroppers, and harvest the energy in the digital - energy signal through energy harvesting; The eavesdropper nodes are used to judge whether each secure user node is communicating through joint eavesdropping.

3. The covert energy routing method in a multi - listener and multi - confidential user scenario according to claim 2, characterized in that, Specifically setting the corresponding routing super - frame in step S1 includes: In the control phase, create a super - frame, perform network synchronization, summarize transmission requirements, generate routing paths and allocate transmission resources, and allocate interference data streams to user transmission requirements; In the transmission phase, divide the data stream evenly into multiple time periods of a set duration, and each time period is further evenly divided into multiple time slots, and each time slot is allocated to the transmission matrix of the data stream generated in the control phase.

4. The covert energy routing method in a multi-listener and multi-secret user scenario according to claim 3, characterized in that, Step S3 specifically includes: S31. Obtain the data stream of the routing layer and the hop - count limit threshold value of the routing path, and initialize the transmission matrix as a non - empty set; S32. Use the breadth - first search algorithm to generate a set of paths where the data stream goes from the starting point to the ending point and the routing hop count is under the hop - count limit threshold value of the routing path; S33. Map the set of paths as a feasible routing path into a column vector; S34. Update the union of the column vector and the transmission matrix as the new transmission matrix.

5. A covert energy routing method in a multi - listener and multi - confidential user scenario according to claim 4, characterized in that Specifically constructing an optimization model for maximizing the total covert uplink throughput data volume of users based on the transmission matrix of the data streams and the energy status of the secure user nodes in step S4 includes: s.t. Among them, Λ S is the total covert uplink throughput data volume of the user, T k is the k-th period divided by the data stream, B is the user allocation matrix, F is the number of periods, K S is the number of secure user nodes, is user s j The covert uplink throughput data volume in period T k is is a 01 variable indicating whether user s j will perform uplink transmission during data stream transmission, N S is the set of secure user nodes, is user s j The energy obtained by energy harvesting during transmission in period T k is is if user s j The energy consumed during communication in period T k is E other is the energy consumption of the user other than communication, is the eavesdropper node w m The eavesdropping error rate of eavesdropping on any secure user node s j is ρ W is the threshold of the covert transmission error rate, N W is the set of eavesdropper nodes, M k is the number of time slots divided by the period, is the time slot divided by period T k is T tra is the total duration of the transmission phase, is the path channel capacity of the i-th path corresponding to the k-th data stream in the transmission matrix, D k is the data volume requirement for the transmission of the k-th data stream.

6. The covert energy routing method in a multi - listener and multi - confidential user scenario according to claim 5, characterized in that, Specifically, the routing path selection result and the time - slot resources allocated to the routing paths obtained by solving in step S4 include: Solve for the maximum covert uplink throughput data volume of a single user assisted by the data stream according to all secure user nodes and data streams; Construct a bipartite graph based on the maximum covert uplink throughput data volume that assists a single user with all data streams, and use the KM algorithm to obtain the maximum matching to generate an optimal user allocation matrix; Substitute the optimal user allocation matrix into the optimization model for maximizing the total covert uplink throughput data volume of users, and solve to obtain the local optimal time slot allocation and the total maximum covert uplink throughput data volume.

7. A covert energy routing method in a multi - listener and multi - confidential user scenario according to claim 6, characterized in that, The specific process of solving for the maximum covert uplink throughput data volume that assists a single user with all data streams for all secure user nodes includes: When not considering energy requirements, construct an optimization model for maximizing the covert uplink throughput data volume that assists a single user with all secure user nodes and data streams, expressed as: s.t. Among them, is the transmission power of the secure user node, is the integrated wireless data and energy transmission routing node r l and the secure user node s j is the channel gain between them, represents whether the routing node r m is activated to transmit data in time slot t i , is the transmission power of the routing node r m , is the channel gain between the routing node r l and the routing node r m , is the expected signal power of the integrated wireless data and energy transmission routing node r m , is the optimal threshold for the eavesdropper node w n to eavesdrop on the secure user node s j , is the noise of the eavesdropper node w n , is the signal power variance of the integrated wireless data and energy transmission routing node r m , is an intermediate variable, is the secure user node s j and the channel gain between the eavesdropper node w n .

8. A covert energy-efficient routing method in a multi-listener and multi-secret user scenario according to claim 7, characterized in that The specific process of constructing a bipartite graph based on the maximum covert uplink throughput data volume that assists a single user with all data streams includes: Use the data streams and secure user nodes as the point sets on both sides of the bipartite graph, and use the set composed of the maximum covert uplink throughput data volume of the secure user nodes under the condition of data stream assistance as the edge set between the point sets on both sides of the bipartite graph.

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