CN112737840B - Internet of vehicles relay selection and safe transmission method based on unmanned aerial vehicle assistance - Google Patents
Internet of vehicles relay selection and safe transmission method based on unmanned aerial vehicle assistance Download PDFInfo
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- H—ELECTRICITY
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- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
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- H—ELECTRICITY
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- H04B7/00—Radio transmission systems, i.e. using radiation field
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- H04B7/18504—Aircraft used as relay or high altitude atmospheric platform
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L63/00—Network architectures or network communication protocols for network security
- H04L63/16—Implementing security features at a particular protocol layer
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- Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
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- Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks
Abstract
The invention discloses an unmanned aerial vehicle-assisted vehicle networking relay selection and safe transmission method which comprises the steps of firstly constructing an unmanned aerial vehicle-assisted vehicle networking model, secondly analyzing and modeling a link service quality model from a source node to a relay node, a node forwarding capacity model from the relay node to a destination node, and a physical layer safety model from the source node to the relay node, from the relay node to the destination node, formalizing a vehicle networking relay selection and safe transmission problem into a multi-target optimization problem related to link service quality, node forwarding capacity and physical layer safety, and solving the problem by a greedy algorithm. The method can improve the success rate of network transmission, reduce the routing overhead and transmission delay, can ensure the safety of user information, and is more suitable for an intelligent transportation system compared with other Internet of vehicles transmission methods.
Description
Technical Field
The invention belongs to the technical field of Internet of vehicles, and particularly relates to a relay selection and safe transmission method for the Internet of vehicles.
Background
Nowadays, society has entered a new era of informatization and intellectualization, and the unmanned aerial vehicle technology also draws high attention of the public. The unmanned aerial vehicle is an unmanned aerial vehicle controlled by a radio system remote control and a self-contained program, can be used for aerial photography to obtain high-definition images by combining remote sensing and remote measuring technologies, and has wide application in the fields of military use, civil use and the like, such as transportation, monitoring, shooting, searching and the like. Unmanned aerial vehicles have gained wide application in the field of internet of vehicles as wireless relays in recent years. Compare with the car networking based on ground communication infrastructure, there is obvious advantage based on supplementary car networking of unmanned aerial vehicle:
(1) The low cost and the miniaturization of the equipment make the practical deployment of unmanned aerial vehicles more feasible. Under the condition that there is large-scale barrier to shelter from and make link quality deteriorate or because natural disasters lead to communication interruption, accessible deployment unmanned aerial vehicle provides wireless stadia connection for remote vehicle, but the vehicle networking application of auxiliary processing emergency and low delay.
(2) The unmanned aerial vehicle with high mobility supports quick response, has good scalability and survivability, can optimally adapt to a communication environment by dynamically adjusting the position of the unmanned aerial vehicle, provides wireless service for a plurality of ground vehicles, and realizes signal coverage.
(3) Use unmanned aerial vehicle to assist mobile communication can improve car networking communication system's capacity greatly, the limited frequency spectrum resource of make full use of to effectively practice thrift mobile terminal's energy at to a great extent, greatly prolonged the car networking and lasted the time of normal work.
However, the actual wireless communication environment of internet of vehicles has a variable complexity, in which there are many uncertain and non-human controlled interference factors, and thus relay selection and security issues using drones for communication have to be considered.
In the prior art, a relay selection scheme based on multi-parameter decision is provided, bandwidth and time delay of candidate relay nodes, a node switching predicted value and corresponding requirements of user nodes are comprehensively considered, performance of the candidate relays is evaluated by using a simple linear weighting function, and the optimal relays are finally obtained. The scheme has better advantages than the traditional scheme in the aspects of system throughput and relay switching times.
In the second prior art, the problem of eavesdropping nodes in the relay system of the unmanned aerial vehicle is solved by adopting a mode that an information source end sends an artificial interference signal to improve the safety capacity of the system. The result shows that the method has better safety capacity than the traditional fixed relay form, and can have the optimal power distribution scheme under the condition that the signal power transmitted by the information source end is certain.
But the problems of the prior art are as follows:
(1) The wireless channel used in the prior art is open, so that when a vehicle transmits private information, all vehicles within a signal coverage range can receive the signal, and a communication system is extremely vulnerable to various security threats, such as eavesdropping, interference, tampering and the like, and information is leaked at risk.
(2) In the second prior art, a decoding and forwarding protocol is adopted, the relay unmanned aerial vehicle demodulates, samples and judges, stores and decodes the received signals into original information, and then retransmits the original information after signal coding and frequency modulation are carried out again. However, the relay unmanned aerial vehicle adopting the scheme needs to completely and correctly decode the original signal before making a forwarding action, which causes a certain signal transmission delay, and fails to utilize the maneuverability of the unmanned aerial vehicle to transmit information in a storage-carrying-forwarding manner.
Disclosure of Invention
In order to overcome the defects of the prior art, the invention provides an unmanned aerial vehicle-assisted vehicle networking relay selection and safe transmission method, which comprises the steps of firstly constructing an unmanned aerial vehicle-assisted vehicle networking network model, secondly analyzing and modeling a link service quality model from a source node to a relay node, a node forwarding capability model from the relay node to a destination node, a physical layer safety model from the source node to the relay node, the relay node to the relay node and the relay node to the destination node, formalizing the vehicle networking relay selection and safe transmission problem into a multi-objective optimization problem related to link service quality, node forwarding capability and physical layer safety, and solving the problem through a greedy algorithm. The method can improve the success rate of network transmission, reduce the routing overhead and transmission delay, can ensure the safety of user information, and is more suitable for an intelligent transportation system compared with other Internet of vehicles transmission methods.
The technical scheme adopted by the invention for solving the technical problem comprises the following steps:
step 1: constructing an Internet of vehicles network model based on unmanned aerial vehicle assistance;
step 1-1: an unmanned aerial vehicle-assisted vehicle network is formed by M network nodes, and the M network nodes form a network node set N k K =1,2. -, M, the network node being a vehicle node or an unmanned aerial vehicle node; the communication range of the unmanned aerial vehicle node is r u The communication range of the vehicle node is r v Nodes within communication range are able to communicate with each other; periodically interacting Hello messages among the network nodes, and discovering available neighbor nodes and real-time link states; the Hello message comprises an information interaction time delay T H Channel capacity C and position information, and updating the information after each Hello message interaction;
when the source node N a When data is sent, the source node N is calculated a And destination node N b A distance L therebetween a,b ：
Wherein N is a Has the coordinates of (N) a (x),N a (y),N a (z))，N b Has the coordinates of (N) b (x),N b (y),N b (z)); if L is a,b <r, then directly sending, otherwise, the source node N a Selecting neighbor node N according to subsequent steps j The relay node is used for relay forwarding;
the selection method of r is as follows:
when source node N a When being unmanned aerial vehicle node, r = r u ；
When source node N a Is a vehicle node, r = r v ；
Step 1-2: the information transmission is carried out by utilizing the mobility of the unmanned aerial vehicle and the vehicle in a storage-carrying-forwarding mode, and the transmission path is expressed as follows:
path{N a ,t n ,k n ,N b }＝{(N a ,t 1 ,k 1 ,N b ),...,(N a ,t n ,k n ,N b )} (2)
wherein k is n Relay node representing the nth hop, t n Represents the time of the nth hop;
step 1-3: from the source node N a To the destination node N b End-to-end transmission delay T a,b Expressed as:
wherein, i represents the ith hop,
indicating the transmission delay of the ith hop,
representing the transmission delay of the ith hop,
indicating the propagation delay of the i-th hop,
indicating the processing delay of the ith hop,
representing the carried time delay of the ith hop;
step 2: constructing a link service quality model from a source node to a relay node based on an unmanned aerial vehicle-assisted Internet of vehicles network model;
step 2-1: according to the Shannon formula, source node N a And relay node N j Channel capacity C between a,j Comprises the following steps:
where B denotes bandwidth, P denotes transmission power, h a,j Representing a slave source node N a To the relay node N j A distance of n 0 Power spectral density representing channel noise, gamma represents path loss factor, h a,j Representing a slave source node N a To the relay node N j Small scale fading of h a,j Expressed as:
wherein h is a,j Obeying an exponential distribution, i.e. | h a,j | 2 ～E(λ)；
Step 2-2: definition R as source node N a When the transmission rate of C a,j The successful forwarding of the information can be realized when the transmission rate is more than or equal to R, and the successful transmission probability is P a,j ，P a,j Expressed as:
wherein the content of the first and second substances,
step 2-3: a source node N a To the relay node N j Is defined as the link quality of service I of the vehicle network based on the assistance of the unmanned plane a,j ，I a,j Expressed as:
wherein, T a,j Representing a source node N a To the destination node N b The end-to-end transmission delay of the network,
and
respectively represent source nodes N a To the relay node N j The transmission delay, the propagation delay and the processing delay;
and step 3: constructing a node forwarding capacity model from a relay node to a destination node based on an unmanned aerial vehicle-assisted internet of vehicles network model;
step 3-1: dividing the effective survival time of the information into l time intervals with the time unit of tau, wherein the mth time interval is expressed as tau m (m is less than or equal to l); node liveness D j (τ m ) Is pointed at tau m Time, relay node N in the network j The frequency of encounters with other nodes is expressed as:
wherein S is j (τ m ) Is expressed at tau m Node N in time j Set of meeting nodes, S j (τ m-1 ) Is expressed at tau m-1 Node N within time j A set of encountered nodes;
step 3-2: node N j At tau m Time and destination node N b Inter-node encounter frequency degree F j,b (τ m ) Expressed as:
wherein E is j,b (τ m ) Is expressed at tau m Node N in time j And destination node N b The number of times of the meeting is counted,
is represented at tau m Node N in time j The number of encounters with all nodes in the network;
step 3-3: relay node N in network j Frequency of encounters with other nodes D j (τ m ) Frequency of encounters with nodes F j,b (τ m ) Defined as the node forwarding capability Q of the drone-based assisted vehicle networking j,b (τ m )，Q j,b (τ m ) Expressed as:
in the formula (10), D j (τ m ) Reflect node N j At tau m The ratio of the number of new nodes encountered in time to the total number, F j,b (τ m ) Reflect node N j At tau m The ratio of the number of encounters with a specific node to the total number of encounters with other nodes in time;
and 4, step 4: based on an unmanned aerial vehicle-assisted Internet of vehicles network model, physical layer security models from a source node to a relay node, from the relay node to the relay node and from the relay node to a destination node are constructed;
step 4-1: assuming that an interception node Eve exists in the Internet of vehicles, intercepting the transmitted Internet of vehicles information; assuming that the codebooks employed by the different network nodes are different, the slave source node N a Secure transmission rate to first hop of first relay node
Expressed as:
wherein L is a,e Representing a source node N a Distance to eavesdropping node Eve, h a,e Representing a slave source node N a Small scale fading, R, to eavesdropping node Eve th Represents the maximum allowable transmission rate, i.e., the safe transmission rate;
step 4-2: the safe transmission rate from the ith-1 relay node to the ith relay node hop
Expressed as:
wherein L is i-1,e Represents the distance h from the i-1 th relay node to the eavesdropping node Eve i-1,e The small-scale fading from the i-1 th relay node to the eavesdropping node Eve is represented;
step 4-3: the safe transmission rate of the nth hop from the last relay node to the destination node
Expressed as:
wherein L is relay-end,e Represents the distance h from the last relay node to the eavesdropping node Eve relay-end,e Representing small-scale fading from the last relay node to the eavesdropping node Eve;
and 5: constructing a target function and an optimization condition of relay selection and safe transmission based on a link service quality model, a node forwarding capability model and a physical layer safety model;
the objective function and optimization condition of relay selection and safe transmission are formalized into an optimization problem under a multi-constraint condition:
wherein E is j Indicating the quality of service of the link I a,j And node forwarding capability Q j,b (τ m ) Delta denotes the minimum probability of successful transmission, delta e (0,1)]，M th A valid time representing the information;
step 6: solving by a greedy algorithm based on an objective function and an optimization condition of relay selection and safe transmission to construct an unmanned aerial vehicle assisted vehicle networking relay selection and safe transmission method;
step 6-1: for the source node N a The number of its neighbor nodes is limited, so equation (14) is expressed as:
wherein r represents the number of neighbor nodes, E j Is a matrix of order r, i.e. E j ＝[I a,1 Q 1,b (τ m ),I a,2 Q 2,b (τ m ),...,I a,r Q r,b (τ m )] 1×r ；
According to equation (5), the optimization problem under one multi-constraint condition formalized by relay selection and secure transmission method is expressed as:
step 6-2: using greedy algorithm, from the objective function
Of medium selection value I a,r Q r,b (τ m ) The largest neighbor node is used as a relay node, and the relay node meets constraint conditions C3.1-C3.5;
and 7: and (6) repeating the step (2) to the step (6) and selecting the relay node of the next hop until the information is transmitted to the destination node.
The invention has the following beneficial effects:
aiming at the problems in the prior art, the invention provides wireless line-of-sight connection for remote vehicles by deploying the unmanned aerial vehicle, can assist in processing emergency and low-delay Internet of vehicles application, and can effectively improve the success rate of network transmission, limit the routing overhead and reduce the transmission delay compared with the existing mechanism on the premise of ensuring the communication safety, the link reliability and the message effectiveness; meanwhile, the signal transmission delay is reduced by adopting a storage-carrying-forwarding mode, the safety of information transmission is improved by utilizing a physical layer safety technology aiming at the problem that a relay system of the unmanned aerial vehicle has eavesdropping nodes, the information safety of a user is guaranteed, and the method is more suitable for an intelligent transportation system compared with other Internet of vehicles transmission methods.
Drawings
FIG. 1 is a flow chart of the method of the present invention.
Fig. 2 is a performance comparison graph comparing transmission success rates of the unmanned-vehicle-assisted-based internet of vehicles, which is provided by the embodiment of the present invention, with a ground-based internet of vehicles (a relay selection and transmission method is adopted in the present invention) and relay selection and transmission are performed by an Epidemic method.
Fig. 3 is a performance comparison graph comparing transmission delay with a ground-based vehicle networking (the relay selection and transmission method of the present invention) and with a vehicle networking based on unmanned aerial vehicle assistance that performs relay selection and transmission by using an Epidemic method according to an embodiment of the present invention.
Fig. 4 is a performance comparison graph comparing the routing overhead with the ground-based internet of vehicles (the relay selection and transmission method of the present invention) and the unmanned-vehicle-assisted-based internet of vehicles that use the Epidemic method for relay selection and transmission, according to the embodiment of the present invention.
Detailed Description
The invention is further illustrated with reference to the following figures and examples.
As shown in fig. 1, a method for relay selection and secure transmission in internet of vehicles based on unmanned aerial vehicle assistance includes the following steps:
step 1: constructing an Internet of vehicles network model based on unmanned aerial vehicle assistance;
step 1-1: an unmanned aerial vehicle-assisted vehicle network is formed by M network nodes, and the M network nodes form a network node set N k K =1,2. -, M, the network node being a vehicle node or an unmanned aerial vehicle node; the communication range of the unmanned aerial vehicle node is r u The communication range of the vehicle node is r v Nodes within communication range are able to communicate with each other; periodically interacting Hello messages between network nodes for discovering available neighborsHome node and real-time link status; the Hello message comprises an information interaction time delay T H Channel capacity C and position information, and updating the information after each Hello message interaction;
when source node N a When data is sent, the source node N is calculated a And destination node N b Distance L between a,b ：
Wherein N is a Has the coordinates of (N) a (x),N a (y),N a (z))，N b Has the coordinates of (N) b (x),N b (y),N b (z)); if L is a,b <r, then directly sending, otherwise, the source node N a Selecting neighbor node N according to subsequent steps j The relay node is used as a relay node for relay forwarding;
the selection method of r is as follows:
when source node N a When being a drone node, r = r u ；
When source node N a Is a vehicle node, r = r v ；
Step 1-2: the information transmission is carried out by utilizing the mobility of the unmanned aerial vehicle and the vehicle in a storage-carrying-forwarding mode, and the transmission path is expressed as follows:
path{N a ,t n ,k n ,N b }＝{(N a ,t 1 ,k 1 ,N b ),...,(N a ,t n ,k n ,N b )} (2)
wherein k is n Relay node representing the nth hop, t n Represents the time of the nth hop;
step 1-3: from the source node N a To the destination node N b End-to-end transmission delay T a,b Expressed as:
wherein, i represents the ith hop,
indicating the transmission delay of the ith hop,
indicating the transmission delay of the ith hop,
indicating the propagation delay of the i-th hop,
indicating the processing delay of the ith hop,
representing the carried time delay of the ith hop;
step 2: constructing a link service quality model from a source node to a relay node based on an unmanned aerial vehicle-assisted Internet of vehicles network model;
step 2-1: according to the Shannon formula, source node N a And relay node N j Channel capacity C between a,j Comprises the following steps:
where B denotes bandwidth, P denotes transmission power, h a,j Representing a slave source node N a To the relay node N j A distance of n 0 Power spectral density representing channel noise, gamma represents a path loss factor, h a,j Representing a slave source node N a To the relay node N j Small scale fading of h a,j Expressed as:
wherein h is a,j Obeying an exponential distribution, i.e. | h a,j | 2 ～E(λ)；
Step 2-2: defining R as a source node N a When the transmission rate of C a,j The successful forwarding of the information can be realized when the transmission rate is more than or equal to R, and the successful transmission probability is P a,j ，P a,j Expressed as:
wherein the content of the first and second substances,
step 2-3: a source node N a To the relay node N j Is defined as the link quality of service I of the vehicle network based on the assistance of the unmanned plane a,j ，I a,j Expressed as:
wherein, T a,j Representing a source node N a To the destination node N b The end-to-end transmission delay of the network,
and
respectively represent source nodes N a To the relay node N j The transmission delay, the propagation delay and the processing delay;
and step 3: constructing a node forwarding capability model from a relay node to a destination node based on an unmanned aerial vehicle-assisted Internet of vehicles network model;
step 3-1: dividing the effective survival time of the information into l time intervals with the time unit of tau, wherein the mth time interval is expressed as tau m (m is less than or equal to l); node activity D j (τ m ) Is pointed at tau m Time, relay node N in the network j The frequency of encounters with other nodes is expressed as：
Wherein S is j (τ m ) Is represented at tau m Node N in time j Set of meeting nodes, S j (τ m-1 ) Is expressed at tau m-1 Node N in time j A set of encountered nodes;
step 3-2: node N j At tau m Time and destination node N b Inter-node encounter frequency degree F j,b (τ m ) Expressed as:
wherein E is j,b (τ m ) Is expressed at tau m Node N in time j And destination node N b The number of times of the meeting is counted,
is expressed at tau m Node N in time j The number of encounters with all nodes in the network;
step 3-3: relay node N in network j Frequency of encounters with other nodes D j (τ m ) Frequency of encounters with nodes F j,b (τ m ) Defined as the node forwarding capability Q of the drone-based assisted vehicle networking j,b (τ m )，Q j,b (τ m ) Expressed as:
in the formula (10), D j (τ m ) Reflect node N j At tau m The ratio of the number of new nodes encountered in time to the total number, F j,b (τ m ) Reflect node N j At tau m The ratio of the number of encounters with a specific node to the total number of encounters with other nodes in time;
and 4, step 4: based on an unmanned aerial vehicle-assisted Internet of vehicles network model, physical layer security models from a source node to a relay node, from the relay node to the relay node and from the relay node to a destination node are constructed;
step 4-1: assuming that an interception node Eve exists in the Internet of vehicles, intercepting the transmitted Internet of vehicles information; assuming that the codebooks employed by the different network nodes are different, the slave source node N a Secure transmission rate to first hop of first relay node
Expressed as:
wherein L is a,e Representing a source node N a Distance to eavesdropping node Eve, h a,e Representing a slave source node N a Small scale fading, R, to eavesdropping node Eve th Represents a maximum transmission rate that can be allowed, i.e., a safe transmission rate;
step 4-2: the safe transmission rate from the ith-1 relay node to the ith relay node hop
Expressed as:
wherein L is i-1,e Represents the distance h from the i-1 th relay node to the eavesdropping node Eve i-1,e The small-scale fading from the i-1 th relay node to the eavesdropping node Eve is represented;
step 4-3: the safe transmission rate of the nth hop from the last relay node to the destination node
Expressed as:
wherein L is relay-end,e Represents the distance h from the last relay node to the eavesdropping node Eve relay-end,e Small-scale fading from the last relay node to the eavesdropping node Eve is represented;
and 5: constructing a target function and an optimization condition of relay selection and safe transmission based on a link service quality model, a node forwarding capability model and a physical layer safety model;
the objective function and optimization condition of relay selection and safe transmission are formalized into an optimization problem under a multi-constraint condition:
wherein E is j Indicating the quality of service of the link I a,j And node forwarding capability Q j,b (τ m ) Delta denotes the minimum probability of successful transmission, delta e (0,1)]，M th A valid time representing the information;
step 6: solving by a greedy algorithm based on an objective function and an optimization condition of relay selection and safe transmission to construct an unmanned aerial vehicle assisted relay selection and safe transmission method in the internet of vehicles;
step 6-1: for the source node N a The number of its neighbor nodes is limited, so equation (14) is expressed as:
wherein r represents the number of neighbor nodes, E j Is a matrix of order r, i.e. E j ＝[I a,1 Q 1,b (τ m ),I a,2 Q 2,b (τ m ),...,I a,r Q r,b (τ m )] 1×r ；
According to equation (5), the optimization problem under one multi-constraint condition formalized by relay selection and secure transmission method is expressed as:
step 6-2: using greedy algorithm, from the objective function
Middle selection value I a,r Q r,b (τ m ) The largest neighbor node is used as a relay node, and the relay node meets constraint conditions C3.1-C3.5;
and 7: and (6) repeating the step (2) to the step (6) and selecting the relay node of the next hop until the information is transmitted to the destination node.
The specific embodiment is as follows:
the embodiment simulates the method for relay selection and safe transmission in the Internet of vehicles based on the assistance of the unmanned aerial vehicle and the existing mechanism based on the same network parameters, and verifies the superiority of the method. The method comprises the following specific steps: the same network parameter is 45km multiplied by 35km, vehicles and unmanned aerial vehicles are randomly placed in a simulation area, the vehicle communication range is 200m, the unmanned aerial vehicle and parked vehicle group communication range is 1000m, the number of vehicles in the environment varies from 0 to 500, the number of unmanned aerial vehicles is 20, the vehicle running speed is 0-50km/h, the unmanned aerial vehicle flying speed is 0-70km/h, the unmanned aerial vehicle flying height is 200m, the hello package interval is 0.1s, the information generation frequency is 30 s/piece, the information size is 1MB-5MB, the information effective time is 5h, and each node cache is 50MB. The data of the following three aspects are counted: 1. a transmission success rate; 2. a transmission delay; 3. the routing overhead. And randomly selecting the target node and the source node, wherein the result is an average value after 10000 times of simulation.
The invention is compared with the performance (transmission success rate, transmission delay and routing overhead) of the ground-based vehicle networking (the invention is adopted as the relay selection and transmission method) and the unmanned aerial vehicle-assisted vehicle networking based on the Epidemic method for relay selection and transmission, as shown in fig. 2 to 4.
As can be seen from fig. 2 to fig. 4, the present invention is superior to the existing mechanisms in terms of transmission success rate, transmission delay, and routing overhead. Specifically, compared with the ground-based internet of vehicles (the relay selection and transmission method adopts the invention), the invention makes full use of flexible deployment of unmanned planes to select the relay nodes, when the number of vehicles reaches 150, the transmission success rate of the invention can be 96%, and at the moment, the transmission success rate of the ground-based internet of vehicles is only 78%. For the unmanned aerial vehicle-assisted vehicle networking which adopts the Epidemic method for relay selection and transmission, the transmission delay is close to that of the unmanned aerial vehicle-assisted vehicle networking, but the flood Fan Jishu is adopted, so that the routing overhead is far higher than that of the unmanned aerial vehicle-assisted vehicle networking, the exponential rise trend is presented, the network resources are quickly consumed in the vehicle networking environment with limited resources, and the network survival time is reduced. In addition, the invention also considers the problem of information security in the transmission process, limits the transmission rate, prevents an eavesdropper from eavesdropping the information by utilizing the physical layer security technology, can effectively reduce the risk of information leakage, and can better meet the requirements of users on future intelligent traffic systems.
To sum up, the method for selecting and safely transmitting the relay in the internet of vehicles based on the assistance of the unmanned aerial vehicle provided by the embodiment of the invention is used for solving the problems in the prior art, firstly, a model of the internet of vehicles based on the assistance of the unmanned aerial vehicle is established, secondly, a link service quality model from a source node to a relay node, a node forwarding capability model from the relay node to a destination node, a physical layer safety model from the source node to the relay node, from the relay node to the relay node and from the relay node to the destination node are analyzed and modeled, the problem of the relay selection and safe transmission in the internet of vehicles is formalized into a multi-target optimization problem related to the link service quality, the node forwarding capability and the physical layer safety, and a greedy algorithm is used for solving.
Claims (1)
1. A relay selection and safe transmission method in Internet of vehicles based on unmanned aerial vehicle assistance is characterized by comprising the following steps:
step 1: constructing an Internet of vehicles network model based on unmanned aerial vehicle assistance;
step 1-1: an unmanned aerial vehicle-assisted vehicle network is formed by M network nodes, and the M network nodes form a network node set N k K =1,2.., M, the network node being a vehicle node or an unmanned aerial vehicle node; the communication range of the unmanned aerial vehicle node is r u The communication range of the vehicle node is r v Nodes within communication range are able to communicate with each other; periodically interacting Hello messages among the network nodes, and discovering available neighbor nodes and real-time link states; the Hello message comprises an information interaction time delay T H Channel capacity C and position information, and updating the information after each Hello message interaction;
when the source node N a When data is transmitted, the source node N is calculated a And destination node N b Distance L between a,b ：
Wherein, N a Has the coordinates of (N) a (x),N a (y),N a (z))，N b Has the coordinates of (N) b (x),N b (y),N b (z)); if L is a,b <r, then directly sending, otherwise, the source node N a Selecting neighbor node N according to subsequent steps j The relay node is used as a relay node for relay forwarding;
the selection method of r is as follows:
when source node N a When being unmanned aerial vehicle node, r = r u ；
When source node N a Is a vehicle node, r = r v ；
Step 1-2: the information transmission is carried out by utilizing the mobility of the unmanned aerial vehicle and the vehicle in a storage-carrying-forwarding mode, and the transmission path is expressed as follows:
path{N a ,t n ,k n ,N b }＝{(N a ,t 1 ,k 1 ,N b ),...,(N a ,t n ,k n ,N b )} (2)
wherein k is n Relay node representing the nth hop, t n Represents the time of the nth hop;
step 1-3: from the source node N a To the destination node N b End-to-end transmission delay T a,b Expressed as:
wherein, i represents the ith hop,
indicating the transmission delay of the ith hop,
indicating the transmission delay of the ith hop,
indicating the propagation delay of the i-th hop,
indicating the processing delay of the ith hop,
representing the carried time delay of the ith hop;
and 2, step: constructing a link service quality model from a source node to a relay node based on an unmanned aerial vehicle-assisted Internet of vehicles network model;
step 2-1: according to the Shannon formula, source node N a And relay node N j Channel capacity C between a,j Comprises the following steps:
where B denotes bandwidth, P denotes transmission power, h a,j Representing a slave source node N a To the relay node N j A distance of n 0 Power spectral density representing channel noise, gamma represents path loss factor, h a,j Representing a slave source node N a To the relay node N j Small scale fading of h a,j Expressed as:
wherein h is a,j Obeying an exponential distribution, i.e. | h a,j | 2 ～E(λ)；
Step 2-2: defining R as a source node N a When the transmission rate of C a,j The successful forwarding of the information can be realized when the transmission rate is more than or equal to R, and the successful transmission probability is P a,j ，P a,j Expressed as:
wherein the content of the first and second substances,
step 2-3: a source node N a To the relay node N j Is defined as the link quality of service I of the vehicle network based on the assistance of the unmanned plane a,j ，I a,j Expressed as:
wherein, T a,j Representing a source node N a To the destination node N b The end-to-end transmission delay of the network,
and
respectively represent source nodes N a To the relay node N j The transmission delay, the propagation delay and the processing delay;
and step 3: constructing a node forwarding capacity model from a relay node to a destination node based on an unmanned aerial vehicle-assisted internet of vehicles network model;
step 3-1: dividing the effective survival time of the information into l time intervals with the time unit of tau, wherein the mth time interval is expressed as tau m M is less than or equal to l; node liveness D j (τ m ) Is pointed at tau m Time, relay node N in the network j The frequency of encounters with other nodes is expressed as:
wherein S is j (τ m ) Is expressed at tau m Node N in time j Set of meeting nodes, S j (τ m-1 ) Is expressed at tau m-1 Node N within time j A set of meeting nodes;
step 3-2: node N j At tau m Time and destination node N b Inter-node encounter frequency degree F j,b (τ m ) Expressed as:
wherein E is j,b (τ m ) Is expressed at tau m Node N in time j And destination node N b The number of times of the meeting is counted,
is expressed at tau m Node N in time j The number of encounters with all nodes in the network;
step 3-3: relay node N in network j Frequency of encounters with other nodes D j (τ m ) Frequency of encounter with nodes F j,b (τ m ) Is defined as the node forwarding capacity Q of the unmanned aerial vehicle-assisted-based vehicle networking j,b (τ m )，Q j,b (τ m ) Expressed as:
in the formula (10), D j (τ m ) Reflect node N j At tau m The ratio of the number of new nodes encountered in time to the total number, F j,b (τ m ) Reflect node N j At tau m The ratio of the number of encounters with a specific node to the total number of encounters with other nodes in time;
and 4, step 4: based on an unmanned aerial vehicle-assisted Internet of vehicles network model, physical layer security models from a source node to a relay node, from the relay node to the relay node and from the relay node to a destination node are constructed;
step 4-1: assuming that an interception node Eve exists in the Internet of vehicles, intercepting the transmitted Internet of vehicles information; assuming that the codebooks employed by the different network nodes are different, the slave source node N a Secure transmission rate to first hop of first relay node
Expressed as:
wherein L is a,e Representing a source node N a Distance to eavesdropping node Eve, h a,e Representing slave source nodesPoint N a Small scale fading, R, to eavesdropping node Eve th Represents the maximum allowable transmission rate, i.e., the safe transmission rate;
step 4-2: the safe transmission rate from the ith-1 relay node to the ith relay node hop
Expressed as:
wherein L is i-1,e Represents the distance h from the i-1 th relay node to the eavesdropping node Eve i-1,e The small-scale fading from the i-1 th relay node to the eavesdropping node Eve is represented;
step 4-3: the safe transmission rate of the nth hop from the last relay node to the destination node
Expressed as:
wherein L is relay-end,e Represents the distance h from the last relay node to the eavesdropping node Eve relay-end,e Small-scale fading from the last relay node to the eavesdropping node Eve is represented;
and 5: constructing a target function and an optimization condition of relay selection and safe transmission based on a link service quality model, a node forwarding capability model and a physical layer safety model;
the objective function and optimization condition of relay selection and safe transmission are formalized into an optimization problem under a multi-constraint condition:
wherein E is j Indicating the quality of service of the link I a,j And node forwarding capability Q j,b (τ m ) Delta denotes the minimum probability of successful transmission, delta e (0,1)]，M th A valid time representing the information;
step 6: solving by a greedy algorithm based on an objective function and an optimization condition of relay selection and safe transmission to construct an unmanned aerial vehicle assisted vehicle networking relay selection and safe transmission method;
step 6-1: for the source node N a The number of its neighbor nodes is limited, so equation (14) is expressed as:
wherein r represents the number of neighbor nodes, E j Is a matrix of order r, i.e. E j ＝[I a,1 Q 1,b (τ m ),I a,2 Q 2,b (τ m ),...,I a,r Q r,b (τ m )] 1×r ；
According to equation (15), the optimization problem under one multi-constraint condition formalized by relay selection and secure transmission method is expressed as:
step 6-2: using greedy algorithm, from the objective function
Of medium selection value I a,r Q r,b (τ m ) The largest neighbor node is used as a relay node, and the relay node meets constraint conditions C3.1-C3.5;
and 7: and (5) repeating the step (2) to the step (6), and selecting the next hop relay node until the information is transmitted to the destination node.
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