CN112654015A - Method and system for selecting cooperative transmission nodes of Internet of vehicles - Google Patents

Method and system for selecting cooperative transmission nodes of Internet of vehicles Download PDF

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CN112654015A
CN112654015A CN202110035368.1A CN202110035368A CN112654015A CN 112654015 A CN112654015 A CN 112654015A CN 202110035368 A CN202110035368 A CN 202110035368A CN 112654015 A CN112654015 A CN 112654015A
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node
vehicles
cooperative transmission
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CN112654015B (en
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张婧
冯欣
承亚林
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Changchun University of Science and Technology
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
    • H04W4/30—Services specially adapted for particular environments, situations or purposes
    • H04W4/40—Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P]
    • H04W4/44—Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P] for communication between vehicles and infrastructures, e.g. vehicle-to-cloud [V2C] or vehicle-to-home [V2H]
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
    • H04W4/30—Services specially adapted for particular environments, situations or purposes
    • H04W4/40—Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P]
    • H04W4/46—Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P] for vehicle-to-vehicle communication [V2V]
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W40/00—Communication routing or communication path finding
    • H04W40/02—Communication route or path selection, e.g. power-based or shortest path routing
    • H04W40/04—Communication route or path selection, e.g. power-based or shortest path routing based on wireless node resources
    • H04W40/08—Communication route or path selection, e.g. power-based or shortest path routing based on wireless node resources based on transmission power
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W40/00—Communication routing or communication path finding
    • H04W40/02—Communication route or path selection, e.g. power-based or shortest path routing
    • H04W40/22—Communication route or path selection, e.g. power-based or shortest path routing using selective relaying for reaching a BTS [Base Transceiver Station] or an access point
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • 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
    • Y02D30/00—Reducing energy consumption in communication networks
    • Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks

Abstract

The invention discloses a method and a system for selecting cooperative transmission nodes of an internet of vehicles, which belong to the technical field of communication of the internet of vehicles, and comprise the following steps: constructing an energy consumption model of node cooperative transmission according to the energy loss of the transmitting circuit; determining the minimum cooperative transmission point number according to the energy consumption model; establishing a virtual Fresnel model for vehicle networking cooperative transmission; determining vehicles of odd Fresnel zones in the virtual Fresnel model according to the Huygens-Fresnel theorem; determining vehicles in the odd Fresnel zones within the communication radius of the source node as candidate nodes; deleting vehicles with the link probability lower than a set threshold value in the candidate nodes to obtain a node set; and selecting the nodes which accord with the minimum cooperative transmission points in the node set as cooperative transmission nodes participating in the Internet of vehicles by utilizing a random matrix. The invention can realize the efficient and stable transmission of information in the cooperative communication process of the Internet of vehicles.

Description

Method and system for selecting cooperative transmission nodes of Internet of vehicles
Technical Field
The invention relates to the technical field of vehicle networking communication, in particular to a method and a system for selecting a cooperative transmission node of a vehicle networking.
Background
The internet of vehicles mainly means that vehicle-mounted equipment on a vehicle completes vehicle-to-vehicle communication, infrastructure-to-vehicle communication and hybrid vehicle communication through a wireless communication technology. The probability of collision accidents of the vehicle can be reduced, the vehicle owner can be helped to navigate in real time, and the efficiency of traffic operation is improved through communication with other vehicles and a network system. Due to its high-speed dynamic network topology changes and variable network density, it poses a great challenge to reliable data transmission. If no roadside access point capable of direct communication exists near the vehicle, the vehicle must rely on vehicle-vehicle multi-hop communication to transmit to a remote node or an infrastructure, the communication mode greatly depends on the performance of a node of the previous hop, and if the vehicle of the previous hop has slow data forwarding, data distortion, data stealing and the node is separated from a multi-hop transmission link, communication breakdown of the node later can be caused, so that stable and reliable transmission of vehicle networking information cannot be guaranteed. The 5G technology is expected to solve the problem, but since the 5G is short-wave communication, the transmission distance is short, the anti-interference capability is limited, and a large number of base stations and roadside access points need to be arranged, which undoubtedly greatly increases the road construction cost.
Cooperative communication, as a powerful technique for improving the performance of a wireless transmission system from the perspective of the physical layer, can provide spatial diversity and wireless transmission performance, thereby avoiding the problems encountered in information transmission as described above. In the cooperative communication mode, each terminal has an information transmitting device and the capability of interacting with adjacent nodes, and the terminals are distributed spatially, so that a virtual cooperative transmission array can be established in a physical layer to realize spatial diversity (also called cooperative diversity) and coding gain. However, when cooperative communication is applied to the car networking technology, cooperative transmission node selection is often inefficient, and vehicle dynamics are not considered.
Therefore, it is urgently needed to solve the difficult problem that the cooperative transmission node is difficult to select or the stability of the effective cooperative transmission node participating in the network environment of the complex and variable vehicle networking is not high.
Disclosure of Invention
The invention aims to provide a method and a system for selecting a cooperative transmission node of an internet of vehicles, so as to realize efficient and stable transmission of information in the cooperative communication process of the internet of vehicles.
In order to achieve the purpose, the invention provides the following scheme:
a method for selecting a cooperative transmission node of a vehicle networking comprises the following steps:
constructing an energy consumption model of node cooperative transmission according to the energy loss of the transmitting circuit;
determining the minimum cooperative transmission point number according to the energy consumption model;
establishing a virtual Fresnel model for vehicle networking cooperative transmission;
determining vehicles of odd Fresnel zones in the virtual Fresnel model according to the Huygens-Fresnel theorem;
determining vehicles in the odd Fresnel zones within the communication radius of the source node as candidate nodes;
deleting vehicles with the link probability lower than a set threshold value in the candidate nodes to obtain a node set;
and selecting the nodes which accord with the minimum cooperative transmission points in the node set as cooperative transmission nodes participating in the Internet of vehicles by utilizing a random matrix.
Optionally, the constructing an energy consumption model of node cooperative transmission according to the loss of the energy of the transmitting circuit specifically includes:
determining an energy consumption model of node cooperative transmission according to the following formula:
Figure BDA0002894067100000021
wherein E istatalEnergy consumption model for cooperative transmission of nodes, EelecFor transmitting loss of circuit energy, EtranN is the number of nodes, and L is the packet length.
Optionally, the determining the minimum cooperative transmission point number according to the energy consumption model specifically includes:
determining energy required for completing the transmission of the primary beam forming information according to the energy consumption model;
and determining the minimum cooperative transmission point number by solving the extreme value of the energy required by finishing the transmission of the primary beam forming information.
Optionally, the determining, according to the energy consumption model, energy required for completing transmission of primary beamforming information specifically includes:
determining the energy required to complete a beamformed information transmission according to the following equation:
Figure BDA0002894067100000031
wherein E isbeam_trThe energy required to complete a beamformed information transmission, EconEnergy consumed by the source node for two communications with other nodes, epsilonfsIs the power amplification factor, dtThe distance from a source node to a target node is defined, eta is the number of the nodes, and the value range of eta is (1, n).
Optionally, the deleting the vehicle whose link probability in the candidate node is lower than a set threshold to obtain a node set specifically includes:
determining the speed change condition of the current vehicle in the candidate node by utilizing a Gaussian Markov process;
determining a truncation probability density function of the vehicle speed according to the vehicle speed change condition;
determining the probability of keeping the two vehicles communicated according to the cutoff probability density function of the vehicle speed and the communication radius of the vehicles;
judging whether the probability is lower than a set threshold value or not to obtain a first judgment result;
if the first judgment result shows that the probability is lower than a set threshold value, deleting the vehicles in the odd Fresnel zones corresponding to the probability;
if the first judgment result shows that the probability is higher than or equal to a set threshold value, reserving the vehicle corresponding to the probability;
the current vehicle is updated with the vehicles in the candidate node and the process returns to the step of determining the vehicle speed of the vehicles in the candidate node using the gaussian markov process.
Optionally, the determining, according to the cut-off probability density function of the vehicle speed and the communication radius of the vehicle, the probability that the two vehicles keep communicating specifically includes:
the probability that two vehicles remain in communication is determined according to the following formula:
Figure BDA0002894067100000032
wherein, PconProbability of keeping communication between two vehicles, R is communication radius of the vehicles, D is actual distance between two vehicles, DmacFor the waiting time delay from the generation of the data from the sending end to the successful transmission to the neighbor node, f (v) is a truncated probability density function of the vehicle speed, and d (v) is an integral sign.
Optionally, the selecting, by using a random matrix, a node in the node set that meets the minimum cooperative transmission point number as a node participating in cooperative transmission of the internet of vehicles specifically includes:
determining an array factor function of the node according with the minimum cooperative transmission point number;
and determining the nodes participating in the cooperative transmission of the Internet of vehicles according to the array factor function.
Optionally, the determining an array factor function of the node that conforms to the minimum number of cooperative transmission points specifically includes:
determining an array factor function according to the following formula:
Figure BDA0002894067100000041
wherein AF (phi, omega) is an array factor function, omega is a weight, NbestFor the minimum number of cooperative transmission points, η has a value range of (1, n), j is a plurality, psiηIs the polar angle of the eta node, λ is the wavelength, dη(phi, theta) is the Euclidean distance from the eta node to the target node, theta is the elevation angle, rηIs the polar meridian of the eta node, phi0Is the azimuth angle of the target node, and phi is the azimuth angle, i.e. the main direction angle of the target node.
A vehicle networking cooperative transmission node selection system, comprising:
the energy consumption model determining module is used for constructing an energy consumption model of node cooperative transmission according to the energy loss of the transmitting circuit;
the minimum cooperative transmission point number determining module is used for determining the minimum cooperative transmission point number according to the energy consumption model;
the virtual Fresnel model establishing module is used for establishing a virtual Fresnel model for vehicle networking cooperative transmission;
the odd Fresnel zone vehicle determining module is used for determining vehicles of odd Fresnel zones in the virtual Fresnel model according to the Huygens-Fresnel theorem;
the candidate node determining module is used for determining vehicles in the odd Fresnel zones within the communication radius of the source node as candidate nodes;
the node set determining module is used for deleting the vehicles with the link probability lower than a set threshold value in the candidate nodes to obtain a node set;
and the participatory Internet of vehicles cooperative transmission node determining module is used for selecting the node which meets the minimum cooperative transmission point number in the node set as a participatory Internet of vehicles cooperative transmission node by utilizing a random matrix.
Optionally, the energy consumption model determining module specifically includes:
an energy consumption model determining unit, configured to determine an energy consumption model for node cooperative transmission according to the following formula:
Figure BDA0002894067100000051
wherein E istatalEnergy consumption model for cooperative transmission of nodes, EelecFor transmitting loss of circuit energy, EtranN is the number of nodes, and L is the packet length.
According to the specific embodiment provided by the invention, the invention discloses the following technical effects:
the invention provides a method and a system for selecting cooperative transmission nodes of a vehicle network, which comprises the following steps of firstly, determining the minimum cooperative transmission point number required by the completion of cooperative transmission of the vehicle network according to an energy consumption model; further determining vehicles in odd Fresnel zones in the virtual Fresnel model according to the Huygens-Fresnel theorem; further determining vehicles in odd Fresnel zones within the communication radius of the source node as candidate nodes; deleting vehicles with the link probability lower than a set threshold value in the candidate nodes to obtain a node set; and selecting the node which accords with the minimum cooperative transmission point number in the node set by utilizing the random matrix as the cooperative transmission node participating in the Internet of vehicles. Due to the fact that the limitation condition of the communication probability is added in the odd Fresnel area, vehicles with communication interruption caused by vehicle speed are eliminated, and the fact that the vehicles participating in cooperative transmission can have good communication capacity is guaranteed, so that stability of the cooperative transmission process is improved. In addition, the node selection is completely carried out based on the communication signal propagation property, so that the node selection process is simplified, and the node selection efficiency is obviously improved.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings needed to be used in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings without inventive exercise.
FIG. 1 is a flowchart of a method for selecting a cooperative transmission node in the Internet of vehicles according to the present invention;
FIG. 2 is a Fresnel principle diagram of a vehicle networking cooperative transmission node selection method according to the invention;
FIG. 3 is a schematic view of a virtual Fresnel model of a vehicle networking cooperative transmission node selection method according to the present invention;
FIG. 4 is a schematic diagram of a three-dimensional Fresnel model of a vehicle networking cooperative transmission node selection method according to the present invention;
FIG. 5 is a diagram of a random array model of a method for selecting nodes for cooperative transmission in the Internet of vehicles according to the present invention;
fig. 6 is a schematic structural diagram of a vehicle networking cooperative transmission node selection system according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The invention aims to provide a method and a system for selecting a cooperative transmission node of an internet of vehicles, so as to realize efficient and stable transmission of information in the cooperative communication process of the internet of vehicles.
In order to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in further detail below.
As shown in fig. 1, the method for selecting a cooperative transmission node in the internet of vehicles provided by the present invention includes:
step 101: and constructing an energy consumption model of node cooperative transmission according to the loss of the energy of the transmitting circuit. Wherein, step 101 specifically includes:
determining an energy consumption model of node cooperative transmission according to the following formula:
Figure BDA0002894067100000061
wherein E istatalEnergy consumption model for cooperative transmission of nodes, EelecFor transmitting loss of circuit energy, EtranN is the number of nodes, and L is the packet length.
In the car networking environment, the coordinates of the information source nodes can be set as (x)s_node,ys_node) The coordinates of the target node may be set to (x)r_node,yr_node) The distance from the information source node to the destination node can be expressed as:
Figure BDA0002894067100000062
because the communication range r of the vehicle is far smaller than the distance d from the source node to the destination nodetTherefore, the distances from the neighboring nodes of the source node to the target node can be considered to be dt. The total energy consumed by the node to transmit 1bit of data to the target node can be expressed as:
Etatal＝LEelec+LEtran＝LEelec+Lεfsdt 2 (2)
where L is the packet length, EelecFor transmitting loss of circuit energy, EtranFor the energy consumed in data transmission, epsilonfsIs the power amplification factor. According to the principle of coherent superposition of electromagnetic waves, when n nodes transmit data to a target node at the same time with the same power, the information received by the target node is gained by n2The power required by the node in transmitting data is the original one
Figure BDA0002894067100000071
That is, the energy required for actually transmitting data by each node is
Figure BDA0002894067100000072
Therefore, the energy consumption model of node cooperative transmission:
Figure BDA0002894067100000073
step 102: and determining the minimum cooperative transmission point number according to the energy consumption model. Wherein, step 102 specifically includes:
and determining the energy required for completing the transmission of the primary beamforming information according to the energy consumption model. The determining, according to the energy consumption model, energy required for completing transmission of the primary beamforming information specifically includes: determining the energy required to complete a beamformed information transmission according to the following equation:
Figure BDA0002894067100000074
wherein E isbeam_trThe energy required to complete a beamformed information transmission, EconEnergy consumed by the source node for two communications with other nodes, epsilonfsIs the power amplification factor, dtThe distance from a source node to a target node is defined, eta is the number of the nodes, and the value range of eta is (1, n).
And determining the minimum cooperative transmission point number by solving the extreme value of the energy required by finishing the transmission of the primary beam forming information.
In the process of carrying out the combined array, a source node sends a data packet to be sent to a destination node to nodes to be selected in the communication radius of the source node in a broadcasting mode, and the nodes reply an acknowledgement message after receiving the information to complete a handshake protocol. Therefore, the source node will communicate with other nodes twice, and the consumed energy is:
Figure BDA0002894067100000075
the energy required to complete a beamforming information transmission is:
Figure BDA0002894067100000076
wherein E isbeam_trThe energy required to complete a beamformed information transmission, EconEnergy consumed by the source node for two communications with other nodes, epsilonfsIs the power amplification factor, dtIs the distance from the source node to the target node, eta is the number of the nodes, and the value range of eta is (1, n)。
And (3) deriving the formula (5) to obtain the number of minimum cooperative transmission points by solving an extremum value:
Figure BDA0002894067100000081
wherein N isbestThe number of points for minimum cooperative transmission.
Step 103: and establishing a virtual Fresnel model for vehicle networking cooperative transmission. 2 running vehicles with actual distance on the road far larger than the communication distance are used as a virtual transmitting end and a virtual receiving end. The visible path between the transmitting end and the receiving end is called a first path, and the electromagnetic wave emitted by the transmitting end passes through the interference of the vehicle p in front of the transmitting end to form a new propagation path, which is called a secondary wave path. Due to the number and position of vehicles in front of the transmitting end, the secondary wave paths form different zones, which are sequentially called as the gamma fresnel zones (gamma ═ 1,2,3.. N) (gamma ∈ N) from inside to outside*)),N*Representing a positive integer.
As shown in fig. 2, according to the huygens-fresnel theorem: spherical waves emitted from a signal transmitting end S can form two paths through interference of any point Q of a wave front, one path is a source wave path, the other path is a secondary wave path, the point Q can be regarded as a secondary wave source, and wave interference formed by the secondary waves at a signal receiving end P can be expressed as:
Figure BDA0002894067100000082
where ξ (r) is the wave interference that the secondary wave will form at the signal receiving end P, ξ0Is a complex amplitude of wave, rcRepresents the distance between the source and the receiver, i represents complex number, k represents wave number
Figure BDA0002894067100000083
λ represents a wavelength. It can be seen that the magnitude of the wave disturbance is inversely proportional to the distance, and the phase change is related to the product of the wave number k and the distance r. The electromagnetic wave emitted from the main wave source,the small complex value disturbance d xi (r) formed to the receiving point P in the small area element ds part of the wave front can be expressed as:
Figure BDA0002894067100000084
wherein R is the distance between the signal transmitting point and the signal receiving point and the tilt factor
Figure BDA0002894067100000085
And x is the external angle of a triangle SQP formed by the signal transmitting end S, the secondary wave source Q and the receiving point P at the receiving point P.
Then the complex-valued perturbation at the reception point P is:
Figure BDA0002894067100000086
where ξ (r) is the complex-valued perturbation at the receiving point P.
Two running vehicles with the actual distance larger than the communication distance are selected on a straight road to serve as a signal transmitting end S and a signal receiving end point P, the visible path of the S and the P is called a first path, namely, the vehicle before the R and the S in the formula 2 is regarded as a secondary wave source Q. From this, a virtual fresnel model in a car networking environment can be constructed as shown in fig. 3. Due to the difference in the number and location of Q' S before S, the secondary paths form different zones, which are referred to as virtual fresnel zones in the vehicle network.
Step 104: and determining the vehicles of the odd Fresnel zones in the virtual Fresnel model according to the Huygens-Fresnel theorem. And selecting the vehicles in the odd Fresnel zones as nodes participating in the cooperation. According to the Huygens-Fresnel theorem, the influence of the secondary waves formed by the nodes in the odd Fresnel regions on the coherent superposition of the source signals can be obtained, and the influence of the secondary waves formed by the nodes in the even Fresnel regions on the coherent cancellation of the source signals can be obtained. Therefore, the vehicles with strengthened signals can be selected in the odd Fresnel areas to form a candidate node set as the participants of vehicle network cooperative communication. Because the source node plays the roles of dispatching command issuing and task issuing, the selected cooperative node needs to be within the communicable range of the source node.
Step 105: and determining vehicles in the odd Fresnel zones within the communication radius of the source node as candidate nodes. According to the Fresnel wave disturbance formula, the phase difference between the source wave and the secondary wave
Figure BDA0002894067100000091
I.e. the secondary wave is advanced with respect to the source wave
Figure BDA0002894067100000092
And the second secondary wave arrives at the receiving point P in advance by pi phases. There are studies showing that when two waves are out of phase
Figure BDA0002894067100000093
Communication distance difference
Figure BDA0002894067100000094
While, the interference generated by the secondary wave source and the source wave are coherently superposed at the receiving point P, and the phase difference of the secondary wave
Figure BDA0002894067100000095
Communication distance difference
Figure BDA0002894067100000096
In time, the source wave is coherently cancelled by the perturbations generated by the source of the secondary waves at the point of reception P. Can deduce that the phase difference between the secondary wave and the source wave is odd number
Figure BDA0002894067100000097
The communication distance difference is odd number
Figure BDA0002894067100000098
During the process, the interference generated by the secondary wave source and the source wave are coherently superposed at the receiving point P, and the phase difference between the secondary wave and the source wave is even number
Figure BDA0002894067100000099
Communication distance differenceEven number of
Figure BDA00028940671000000910
During the process, the interference generated by the secondary wave source and the source wave are in coherent cancellation at the receiving point P, that is, the vehicles in the odd fresnel regions play a role in signal enhancement for the cooperative transmission of the internet of vehicles, and the vehicles in the even fresnel regions have an interference role for the cooperative transmission of the internet of vehicles (the odd and even fresnel regions are defined below). As shown in fig. 4: s and P are transmitting points and receiving points of the virtual Fresnel model of the Internet of vehicles, Q is a primary wave source of the boundary of the first virtual Fresnel zone S1, the first virtual Fresnel zone is intercepted by a plane which is perpendicular to the straight line SP and passes through the point Q, a section circle C1 is obtained, and the radius of C1 is the radius of the first Fresnel zone. The Fresnel area radius definition formula is given:
Figure BDA0002894067100000101
obtaining:
Figure BDA0002894067100000102
where Q' is the projection of Q on the straight line SP, h1For the projection length, the distance between SPs is defined as d, d1Distance between SQ', d2Is the distance between Q' P and satisfies d ═ d1+d2If and only if
Figure BDA0002894067100000103
When h is present1Maximum is
Figure BDA0002894067100000104
In the same way, the radius of the nth virtual fresnel zone is as follows:
Figure BDA0002894067100000105
the 1 st, 2 nd and 3 … n Fresnel regions are sequentially determined according to the subscript of the required radius, namely the Fresnel region can be divided into an odd Fresnel region and an even Fresnel region. After the radius of the Fresnel area is determined, the odd Fresnel area can be determinedThe vehicles within are candidate nodes participating in the vehicle network cooperative transmission. While the source node plays the role of command issuing and scheduling in the system, the selected node must be guaranteed to be within the communicable range of the source node. I.e., the set of nodes within the communication radius of the odd fresnel zone and the source node, are the points considered by this patent to participate in the cooperative transmission of the vehicle network.
Step 106: and deleting the vehicles with the link probability lower than a set threshold value in the candidate nodes to obtain a node set. Discretizing continuous sampling time into equal time intervals, and discretizing continuous vehicle speed in the same way (the discretization of the vehicle speed is independent of time) under the assumption that the state of the vehicle (the vehicle speed and the route) and the network topology of the vehicle cannot be changed in the same time interval. In order to better obtain the dynamic variation trend of the vehicle speed, a Gaussian Markov process is adopted for analysis. Assuming that the vehicle speed follows normal distribution, the distribution of the vehicle speed can be described by adopting a truncation probability density function of positive distribution in consideration of the actual condition of the road and the condition that the vehicle speed is too high or too low can not occur. The communication probability among the vehicles can be obtained, in order to enable the cooperative transmission performance to be more stable, the vehicles with the connection probability lower than a set threshold value are deleted, and a node set participating in the cooperative transmission of the Internet of vehicles is obtained. Because the selected nodes participating in the cooperative transmission are vehicles in the driving process, a certain safety distance is considered (only the same lane problem is considered, and the situations of adjacent lanes, sudden lane change and the like are not considered). Step 106 specifically includes:
and determining the vehicle speed change condition of the current vehicle in the candidate node by utilizing a Gaussian Markov process.
And determining a truncation probability density function of the vehicle speed according to the vehicle speed change condition.
And determining the probability of keeping the two vehicles communicated according to the cutoff probability density function of the vehicle speed and the communication radius of the vehicles. The determining the probability that the two vehicles are communicated according to the cutoff probability density function of the vehicle speed and the communication radius of the vehicles specifically comprises the following steps: the probability that two vehicles remain in communication is determined according to the following formula:
Figure BDA0002894067100000111
wherein, PconProbability of keeping communication between two vehicles, R is communication radius of the vehicles, D is actual distance between two vehicles, DmacFor the waiting time delay from the generation of the data from the sending end to the successful transmission to the neighbor node, f (v) is a truncated probability density function of the vehicle speed, and d (v) is an integral sign.
And judging whether the probability is lower than a set threshold value or not to obtain a first judgment result. And if the first judgment result shows that the probability is lower than a set threshold value, deleting the vehicles in the odd Fresnel zone corresponding to the probability. And if the first judgment result shows that the probability is higher than or equal to a set threshold value, reserving the vehicle corresponding to the probability.
The current vehicle is updated with the vehicles in the candidate node and the process returns to the step of determining the vehicle speed of the vehicles in the candidate node using the gaussian markov process.
More specifically, the continuous sampling time T is discretized into equal time intervals, and the vector T is used as { T }1,t2,t3,...,tτ+1Denotes that the vehicle situation on the road can be V ═ Vs,vwDenotes wherein v issIndicating the state of the vehicle, vwRepresenting the topology of the network. Assuming the same time interval tτIn that the vehicles on the road have a state v corresponding to this time intervalstτ(speed, route) and network topology v of the vehiclewtτWithin the same time interval vstτAnd vwtτNo change occurs. Since the motion information of the vehicle has certain historical property and instantaneity, in order to better describe the change situation of the vehicle speed in different time intervals, a Gaussian Markov process is adopted to analyze the vehicle speed.
Figure BDA0002894067100000112
Wherein v isstτTo representVehicle at current time velocity vstτ-1Indicating the vehicle speed (v) at the previous momentstτ,vstτ-1∈vst) α represents the degree of time-dependence of the moving speed of the vehicle and has a value range of (0,1), μ and σ are the mean and variance of the speed, and ω isiRepresenting a velocity independent gaussian random variable with mean 0 and variance 1. Assuming that the distribution of the vehicle speed on the road is in accordance with normal distribution, the probability density function is as follows:
Figure BDA0002894067100000113
wherein f is*(v) Is a probability density function, v is the vehicle speed,
Figure BDA0002894067100000121
and σ is the mean and variance of the vehicle speed satisfying the above normal distribution. Considering the actual condition of the road, the requirement of meeting the safe driving distance in the driving process of the vehicle, the reaction time of a driver in an emergency situation and the like is formulated by a braking distance formula
Figure BDA0002894067100000122
The maximum running speed can be obtained. The maximum vehicle speed meeting the requirements of the patent is set as vmaxMinimum vehicle speed vminThe cutoff probability density function describing vehicle speed is then:
Figure BDA0002894067100000123
wherein erf is the cumulative distribution function of the standard normal distribution, f (v) is the truncation probability density function of the vehicle speed, and the functions are developed and simplified to obtain:
Figure BDA0002894067100000124
then the probability of keeping a communication between two vehicles is:
Figure BDA0002894067100000125
wherein d is the actual distance between two workshops, PconProbability of communication between two vehicles, D (v) is integral sign, R is communication radius of vehicle, DmacIndicating the latency from the generation of data from the sender to the successful transmission to the neighboring node. Vehicles with link probability lower than a set threshold are deleted from the odd Fresnel area, namely, the vehicles participating in cooperative transmission need to meet link probability PconZeta is larger than or equal to, the communication state of the vehicle is considered to be good, the stability of cooperative transmission can be ensured, and the node set is obtained and is marked as NcAnd ζ represents a set threshold value.
Step 107: and selecting the nodes which accord with the minimum cooperative transmission points in the node set as cooperative transmission nodes participating in the Internet of vehicles by utilizing a random matrix. Wherein, step 107 specifically comprises:
and determining an array factor function of the node according with the minimum cooperative transmission point number. The determining an array factor function of the node according with the minimum coordinated transmission point number specifically includes: determining an array factor function according to the following formula:
Figure BDA0002894067100000131
wherein AF (phi, omega) is an array factor function, omega is a weight, NbestFor the minimum number of cooperative transmission points, η has a value range of (1, n), j is a plurality, psiηIs the polar angle of the eta node, λ is the wavelength, dη(phi, theta) is the Euclidean distance from the eta node to the target node, theta is the elevation angle, rηIs the polar meridian of the eta node, phi0Is the azimuth angle of the target node, and phi is the azimuth angle, i.e. the main direction angle of the target node.
And determining the nodes participating in the cooperative transmission of the Internet of vehicles according to the array factor function.
In the normal case, NcWill be greater than NbestIn N atcInternal random array selection coincidence with NbestA number of nodes participate in the cooperative transmission. As shown in fig. 5: establishing polar coordinates by taking the source node as a pole, and setting the polar coordinates of the nodes participating in cooperation as (r, psi), wherein the polar diameter
Figure BDA0002894067100000132
Polar angle
Figure BDA0002894067100000133
Assuming that the spherical coordinates of the target node are (A)dis,θ0,φ0) Distance from source node to target node can be usedηExpressed, the euclidean distance from the nth node participating in the cooperative transmission of the internet of vehicles to the destination node can be expressed as:
Figure BDA0002894067100000134
wherein d isη(phi, theta) is the Euclidean distance from the eta node participating in the cooperative transmission of the Internet of vehicles to the destination node, rηIs the polar meridian of the eta node.
Let the initial phase of the node be:
Figure BDA0002894067100000135
wherein psiηIs the initial phase of the node.
The phases of signals sent by all nodes participating in cooperative transmission and reaching a destination node are assumed to be synchronous, so that errors generated by coherent superposition of electromagnetic waves are reduced to a certain extent. Then N isbestThe Array Factor (AF) of an array of nodes in the plane x-y can be expressed as:
Figure BDA0002894067100000136
where ω is the weight. And determining the vehicles specifically participating in the cooperative transmission of the Internet of vehicles according to the array factor function (AF) and the weight omega.
As shown in fig. 6, the system for selecting a cooperative transmission node in the internet of vehicles provided by the present invention includes:
and the energy consumption model determining module 601 is configured to construct an energy consumption model for node cooperative transmission according to the loss of the energy of the transmitting circuit. The energy consumption model determining module 601 specifically includes:
an energy consumption model determining unit, configured to determine an energy consumption model for node cooperative transmission according to the following formula:
Figure BDA0002894067100000141
wherein E istatalEnergy consumption model for cooperative transmission of nodes, EelecFor transmitting loss of circuit energy, EtranN is the number of nodes, and L is the packet length.
A minimum cooperative transmission point number determining module 602, configured to determine a minimum cooperative transmission point number according to the energy consumption model.
And a virtual fresnel model establishing module 603, configured to establish a virtual fresnel model for vehicle networking cooperative transmission.
An odd fresnel zone vehicle determining module 604, configured to determine vehicles of odd fresnel zones in the virtual fresnel model according to huygens-fresnel theorem.
A candidate node determining module 605, configured to determine vehicles in the odd fresnel zone within the communication radius of the source node as candidate nodes.
And a node set determining module 606, configured to delete the vehicle with the link probability lower than a set threshold in the candidate nodes, so as to obtain a node set.
And a participating vehicle networking cooperative transmission node determining module 607, configured to select, by using a random matrix, a node in the node set that meets the minimum cooperative transmission point number as a participating vehicle networking cooperative transmission node.
The method mainly solves the problem that the cooperative transmission node is difficult to select or the stability of the effective cooperative transmission node is not high in the network environment with complicated and changeable vehicle networking. According to the essential characteristics of signal propagation and the link environment of dynamic change in the vehicle running process, the node vehicles which participate in the cooperative transmission of the Internet of vehicles can be efficiently and stably selected, and a foundation is laid for the stable transmission of information in the environment of the Internet of vehicles. The method comprises the steps of firstly determining the minimum number of nodes required for completing cooperative transmission of the Internet of vehicles according to an energy consumption model, further proposing a virtual Fresnel model of the Internet of vehicles according to the Huygens-Fresnel theorem, and forming a cooperative transmission candidate node set by nodes in odd Fresnel regions. And (3) providing a dynamic link model based on the vehicle speed in consideration of the dynamic network topological structure of the mobile vehicle, deleting nodes with the link probability lower than a set threshold value in an odd Fresnel region, and selecting a node set participating in the cooperative transmission of the Internet of vehicles from the candidate node sets according to the node number determined in the first step. The invention has the following advantages:
the method has the advantages that: the node selection efficiency is remarkably improved (the node selection is completely based on the communication signal propagation property, the selection condition is limited to be determined only by the position of the selected vehicle in front of the transmitting end, the communication times between the source node and the cooperative node and the network topology updating time are reduced, and the node selection process is simplified further).
The method has the advantages that: the communication is more stable (because the limitation condition of the communication probability is added in the odd Fresnel area, the vehicles with communication interruption caused by the vehicle speed are deleted, and the vehicles participating in the cooperative transmission can have good communication capacity, so that the stability of the cooperative transmission process is improved).
The embodiments in the present description are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other. For the system disclosed by the embodiment, the description is relatively simple because the system corresponds to the method disclosed by the embodiment, and the relevant points can be referred to the method part for description.
The principles and embodiments of the present invention have been described herein using specific examples, which are provided only to help understand the method and the core concept of the present invention; meanwhile, for a person skilled in the art, according to the idea of the present invention, the specific embodiments and the application range may be changed. In view of the above, the present disclosure should not be construed as limiting the invention.

Claims (10)

1. A method for selecting a cooperative transmission node in the Internet of vehicles is characterized by comprising the following steps:
constructing an energy consumption model of node cooperative transmission according to the energy loss of the transmitting circuit;
determining the minimum cooperative transmission point number according to the energy consumption model;
establishing a virtual Fresnel model for vehicle networking cooperative transmission;
determining vehicles of odd Fresnel zones in the virtual Fresnel model according to the Huygens-Fresnel theorem;
determining vehicles in the odd Fresnel zones within the communication radius of the source node as candidate nodes;
deleting vehicles with the link probability lower than a set threshold value in the candidate nodes to obtain a node set;
and selecting the nodes which accord with the minimum cooperative transmission points in the node set as cooperative transmission nodes participating in the Internet of vehicles by utilizing a random matrix.
2. The method for selecting the nodes in the cooperative transmission of the internet of vehicles according to claim 1, wherein the constructing an energy consumption model of the node cooperative transmission according to the loss of the energy of the transmitting circuit specifically comprises:
determining an energy consumption model of node cooperative transmission according to the following formula:
Figure FDA0002894067090000011
wherein E istatalEnergy of cooperative transmission for nodesConsumption model of quantity EelecFor transmitting loss of circuit energy, EtranN is the number of nodes, and L is the packet length.
3. The vehicle networking cooperative transmission node selection method according to claim 2, wherein the determining a minimum cooperative transmission point number according to the energy consumption model specifically includes:
determining energy required for completing the transmission of the primary beam forming information according to the energy consumption model;
and determining the minimum cooperative transmission point number by solving the extreme value of the energy required by finishing the transmission of the primary beam forming information.
4. The method for selecting the cooperative transmission node in the internet of vehicles according to claim 3, wherein the determining the energy required for completing the transmission of the primary beamforming information according to the energy consumption model specifically comprises:
determining the energy required to complete a beamformed information transmission according to the following equation:
Figure FDA0002894067090000021
wherein E isbeam_trThe energy required to complete a beamformed information transmission, EconEnergy consumed by the source node for two communications with other nodes, epsilonfsIs the power amplification factor, dtThe distance from a source node to a target node is defined, eta is the number of the nodes, and the value range of eta is (1, n).
5. The method for selecting the nodes in the vehicle networking cooperative transmission according to claim 4, wherein the deleting the vehicles with the link probability lower than a set threshold from the candidate nodes to obtain the node set specifically comprises:
determining the speed change condition of the current vehicle in the candidate node by utilizing a Gaussian Markov process;
determining a truncation probability density function of the vehicle speed according to the vehicle speed change condition;
determining the probability of keeping the two vehicles communicated according to the cutoff probability density function of the vehicle speed and the communication radius of the vehicles;
judging whether the probability is lower than a set threshold value or not to obtain a first judgment result;
if the first judgment result shows that the probability is lower than a set threshold value, deleting the vehicles in the odd Fresnel zones corresponding to the probability;
if the first judgment result shows that the probability is higher than or equal to a set threshold value, reserving the vehicle corresponding to the probability;
the current vehicle is updated with the vehicles in the candidate node and the process returns to the step of determining the vehicle speed of the vehicles in the candidate node using the gaussian markov process.
6. The method for selecting the nodes in the cooperative transmission of the internet of vehicles according to claim 5, wherein the determining the probability that two vehicles keep communicating according to the cutoff probability density function of the vehicle speed and the communication radius of the vehicles specifically comprises:
the probability that two vehicles remain in communication is determined according to the following formula:
Figure FDA0002894067090000022
wherein, PconProbability of keeping communication between two vehicles, R is communication radius of the vehicles, D is actual distance between two vehicles, DmacFor the waiting time delay from the generation of the data from the sending end to the successful transmission to the neighbor node, f (v) is a truncated probability density function of the vehicle speed, and d (v) is an integral sign.
7. The method for selecting the cooperative transmission node in the internet of vehicles according to claim 6, wherein the selecting the node in the node set that meets the minimum cooperative transmission point number as the cooperative transmission node participating in the internet of vehicles by using a random matrix specifically comprises:
determining an array factor function of the node according with the minimum cooperative transmission point number;
and determining the nodes participating in the cooperative transmission of the Internet of vehicles according to the array factor function.
8. The method for selecting the cooperative transmission node in the internet of vehicles according to claim 7, wherein the determining an array factor function of the node that meets the minimum cooperative transmission point number specifically comprises:
determining an array factor function according to the following formula:
Figure FDA0002894067090000031
wherein AF (phi, omega) is an array factor function, omega is a weight, NbestFor the minimum number of cooperative transmission points, η has a value range of (1, n), j is a plurality, psiηIs the polar angle of the eta node, λ is the wavelength, dη(phi, theta) is the Euclidean distance from the eta node to the target node, theta is the elevation angle, rηIs the polar meridian of the eta node, phi0Is the azimuth angle of the target node, and phi is the azimuth angle, i.e. the main direction angle of the target node.
9. A vehicle networking cooperative transmission node selection system, comprising:
the energy consumption model determining module is used for constructing an energy consumption model of node cooperative transmission according to the energy loss of the transmitting circuit;
the minimum cooperative transmission point number determining module is used for determining the minimum cooperative transmission point number according to the energy consumption model;
the virtual Fresnel model establishing module is used for establishing a virtual Fresnel model for vehicle networking cooperative transmission;
the odd Fresnel zone vehicle determining module is used for determining vehicles of odd Fresnel zones in the virtual Fresnel model according to the Huygens-Fresnel theorem;
the candidate node determining module is used for determining vehicles in the odd Fresnel zones within the communication radius of the source node as candidate nodes;
the node set determining module is used for deleting the vehicles with the link probability lower than a set threshold value in the candidate nodes to obtain a node set;
and the participatory Internet of vehicles cooperative transmission node determining module is used for selecting the node which meets the minimum cooperative transmission point number in the node set as a participatory Internet of vehicles cooperative transmission node by utilizing a random matrix.
10. The system for selecting the vehicle networking cooperative transmission node according to claim 9, wherein the energy consumption model determining module specifically comprises:
an energy consumption model determining unit, configured to determine an energy consumption model for node cooperative transmission according to the following formula:
Figure FDA0002894067090000041
wherein E istatalEnergy consumption model for cooperative transmission of nodes, EelecFor transmitting loss of circuit energy, EtranN is the number of nodes, and L is the packet length.
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