CN118283565A - Internet of vehicles information processing method and device and electronic equipment - Google Patents
Internet of vehicles information processing method and device and electronic equipment Download PDFInfo
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Abstract
The disclosure relates to a method and a device for processing information of the internet of vehicles and electronic equipment, and relates to the technical field of the internet of vehicles, wherein the method comprises the following steps: receiving the internet of vehicles information transmitted by the transmitting node through the system node, wherein the system node comprises a first relay node, an edge node and a second relay node; the variable matrixes corresponding to the transmitting node, the first relay node, the edge node and the second relay node are diagonalized through channel parallelization, so that the mean square error value of the information of the Internet of vehicles meets an optimization target, the optimization target is that the mean square error value is smaller than a preset mean square error value, and by applying the scheme of the present disclosure, a large-scale information transmission from the transmitting node to the receiving node can be realized, the calculation is effectively simplified, the calculation complexity is reduced, and the consumption of calculation resources is reduced.
Description
Technical Field
The present application relates to the field of internet of vehicles, and in particular, to an internet of vehicles information processing method, an internet of vehicles information processing device, and an electronic device.
Background
With the wide spread of terminal devices such as smartphones and automobiles and the blowout growth of new smart applications (e.g. autopilot, augmented/virtual reality), it is a critical issue to address these applications that require sustainable high performance computing and are time-sensitive. The edge cloud is used as a new model, and by utilizing the cloud function of the edge equipment (such as a base station), sufficient capacity is provided to help the terminal equipment to complete the expansion of the computing storage capacity, so that the time delay and the energy consumption are effectively reduced, and the edge cloud is widely applied to the field of the Internet of vehicles.
However, in complex internet of vehicles scenarios, such as intersection communication, direct communication between vehicles may be limited due to obstacle occlusion or line of sight problems, where information exchange needs to be accomplished by means of an edge node such as a base station.
In the existing internet of vehicles, when the internet of vehicles information exchange is carried out through the edge nodes, only the internet of vehicles information exchange between two vehicles nearby the same edge node can be allowed, so that the sharing range of the internet of vehicles information is smaller, and the large-range vehicle collaborative scheduling cannot be realized. In addition, in the prior art, the accuracy of information exchange of the Internet of vehicles is generally represented by adopting minimum mean square error, and the accuracy of information exchange of a system is improved by minimizing the minimum mean square error, but the algorithm of the existing scheme is high in complexity, so that the consumption of computing resources is high.
Disclosure of Invention
In view of the above, the application provides a method, a device and an electronic device for processing information of the internet of vehicles, which mainly aim to solve the technical problems of smaller sharing range of the information of the internet of vehicles at present and high algorithm complexity of the existing scheme, which results in large consumption of computing resources.
According to a first aspect of the present disclosure, there is provided an internet of vehicles information processing method applied to a receiving node side for execution, the method including:
Receiving the internet of vehicles information transmitted by the transmitting node through the system node, wherein the system node comprises a first relay node, an edge node and a second relay node;
And diagonalizing the variable matrixes corresponding to the transmitting node, the first relay node, the edge node and the second relay node through channel parallelization so that the mean square error value of the Internet of vehicles information meets an optimization target, wherein the optimization target is that the mean square error value is smaller than a preset mean square error value.
According to a second aspect of the present disclosure, there is provided an internet of vehicles information processing method applied to a transmitting node side for execution, the method including:
and transmitting the internet of vehicles information transmitted by the system node to a receiving node, and diagonalizing the variable matrixes corresponding to the transmitting node, the first relay node, the edge node and the second relay node of the system node through channel parallelization to enable the mean square error value of the internet of vehicles information to meet an optimization target, wherein the optimization target is that the mean square error value is smaller than a preset mean square error value, and the system node comprises the first relay node, the edge node and the second relay node.
According to a third aspect of the present disclosure, there is provided an internet of vehicles information processing apparatus applied to a receiving node side, the apparatus comprising:
The system comprises a receiving module, a transmitting module and a receiving module, wherein the receiving module is used for receiving the internet-of-vehicles information transmitted by a transmitting node through a system node, and the system node comprises a first relay node, an edge node and a second relay node;
and the processing module is used for diagonalizing the variable matrixes corresponding to the transmitting node, the first relay node, the edge node and the second relay node through channel parallelization so as to enable the mean square error value of the internet of vehicles information to meet an optimization target, wherein the optimization target is that the mean square error value is smaller than a preset mean square error value.
According to a fourth aspect of the present disclosure, there is provided an internet of vehicles information processing apparatus applied to a transmitting node side, the apparatus comprising:
The system comprises a transmitting module, a receiving module and a receiving module, wherein the transmitting module is used for transmitting the internet of vehicles information transmitted by a system node to the receiving node, so that the variable matrixes corresponding to the transmitting node, a first relay node, an edge node and a second relay node of the system node are diagonalized through channel parallelization, and the mean square error value of the internet of vehicles information meets an optimization target, the optimization target is that the mean square error value is smaller than a preset mean square error value, and the system node comprises the first relay node, the edge node and the second relay node.
According to a fifth aspect of the present disclosure, there is provided an electronic device comprising: at least one processor; and a memory communicatively coupled to the at least one processor; wherein the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of the first aspect or the method of the second aspect.
According to a sixth aspect of the present disclosure, there is provided a non-transitory computer readable storage medium storing computer instructions for causing a computer to perform the method of the foregoing first aspect, or to perform the method of the foregoing second aspect.
According to a seventh aspect of the present disclosure, there is provided a computer program product comprising a computer program which, when executed by a processor, implements a method as in the first aspect described above, or which, when executed, implements a method as in the second aspect described above.
Compared with the prior art, the method and the device for processing the information of the Internet of vehicles and the electronic equipment have the advantages that the information of the Internet of vehicles transmitted through the system node and transmitted by the transmitting node is received, wherein the system node comprises a first relay node, an edge node and a second relay node; and diagonalizing variable matrixes corresponding to the transmitting node, the first relay node, the edge node and the second relay node through channel parallelization so that the mean square error value of the information of the internet of vehicles meets an optimization target, wherein the optimization target is that the mean square error value is smaller than a preset mean square error value. For the scheme of the disclosure, two relay nodes are utilized to combine with an edge node, so that large-range information transmission from a transmitting node to a receiving node is realized; in channel parallelization, by diagonalizing the variable matrix, calculation can be effectively simplified, and calculation complexity is reduced, so that calculation resource consumption is reduced.
The foregoing description is only an overview of the present application, and is intended to be implemented in accordance with the teachings of the present application in order that the same may be more clearly understood and to make the same and other objects, features and advantages of the present application more readily apparent.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the application and together with the description, serve to explain the principles of the application.
In order to more clearly illustrate the embodiments of the application or the technical solutions of the prior art, the drawings which are used in the description of the embodiments or the prior art will be briefly described, and it will be obvious to a person skilled in the art that other drawings can be obtained from these drawings without inventive effort.
Fig. 1 is a flow chart of an information processing method of internet of vehicles according to an embodiment of the disclosure;
fig. 2 is a schematic diagram of a communication scenario of a vehicle intersection provided in an embodiment of the disclosure;
Fig. 3 is a flow chart of an information processing method of internet of vehicles according to an embodiment of the disclosure;
fig. 4 is a flowchart of an edge cloud internet of vehicles beamforming optimization method and system provided by an embodiment of the present disclosure;
fig. 5 is a flow chart of an information processing method of internet of vehicles according to an embodiment of the disclosure;
Fig. 6 is a schematic structural diagram of an information processing apparatus for internet of vehicles according to an embodiment of the present disclosure;
Fig. 7 is a schematic structural diagram of an information processing apparatus for internet of vehicles according to an embodiment of the present disclosure.
Detailed Description
Exemplary embodiments of the present disclosure are described below in conjunction with the accompanying drawings, which include various details of the embodiments of the present disclosure to facilitate understanding, and should be considered as merely exemplary. Accordingly, one of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the present disclosure. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness. It should be noted that, without conflict, the embodiments of the present disclosure and features in the embodiments may be combined with each other.
The following describes an internet of vehicles information processing method, an internet of vehicles information processing device and electronic equipment according to the embodiments of the present disclosure with reference to the accompanying drawings.
The invention provides a method, a device and electronic equipment for processing information of the Internet of vehicles, which utilize two relay nodes to combine with an edge node so as to realize large-scale information transmission from a transmitting node to a receiving node; in channel parallelization, by diagonalizing the variable matrix, calculation can be effectively simplified, and calculation complexity is reduced, so that calculation resource consumption is reduced.
As shown in fig. 1, an embodiment of the present disclosure provides an information processing method of internet of vehicles, applied to a receiving node side for execution, the method including:
step 101, receiving the internet of vehicles information transmitted by the transmitting node through the system node, wherein the system node comprises a first relay node, an edge node and a second relay node.
The transmitting node may be a vehicle or a road side device initiating communication in the internet of vehicles system, etc.
The internet of vehicles (V2X) may be vehicle-to-X communications, and the internet of vehicles (V2X) may include vehicle-to-vehicle (V2V), vehicle-to-road side infrastructure (V2I), vehicle-to-pedestrian (V2P), vehicle-to-network (V2N), and the like communications.
The internet of vehicles information may be data related to vehicles and traffic environments collected and processed through various information sensors, vehicle-mounted terminals, road side devices, etc. mounted on the vehicles, including, but not limited to, positions, speeds, traveling directions of the vehicles, road conditions, traffic signals, environmental perception information (such as weather conditions, visibility, etc.), etc.
A relay node may be a device that functions to forward and enhance signals.
The edge node may be a data processing node close to the vehicle or the road side device, and may be responsible for collecting the internet of vehicles information from the transmitting node, processing the internet of vehicles information, and forwarding the processed internet of vehicles information to the next relay node.
For the embodiment of the disclosure, in order to consider the remote communication requirement of the actual internet of vehicles at the intersection, and meet the data sharing requirement under the condition that the vehicle or other terminal equipment is far away from the edge node (such as a road side unit or a mobile base station, etc.), the network coverage is further expanded without adding additional infrastructure, an edge cloud internet of vehicles double-hop relay communication system model is designed, the transmission of data between the double-hop relay auxiliary terminal equipment is utilized, and the link stability is improved, as shown in fig. 2.
In the double-hop relay system, data transmission can be performed through two relay nodes (namely a relay R1 and a relay R2), source equipment (namely a transmitting node such as a user S1) can send internet-of-vehicle information to a first relay node (such as a relay R1), then the first relay node (such as a relay R1) can forward the internet-of-vehicle information to an edge node, the edge node can forward the internet-of-vehicle information to a second relay node (such as a relay R2), finally the second relay node (such as a relay R2) can send the internet-of-vehicle information to target terminal equipment (namely a receiving node such as a user S2), and by the method, the communication distance can be expanded, direct communication barriers (such as building shielding or weak signals) can be overcome, and the signal quality can be improved.
And 102, diagonalizing variable matrixes corresponding to the transmitting node, the first relay node, the edge node and the second relay node through channel parallelization so that the mean square error value of the information of the Internet of vehicles meets the optimization target.
Wherein, the optimization target can be that the mean square error value is smaller than a preset mean square error value; the mean square error value (Mean Squared Error, MSE) may be an indicator for measuring the difference between the predicted value and the actual value, and in this case, the mean square error value may be used to measure the difference between the received signal and the transmitted signal during signal transmission. The preset mean square error value may be a preset threshold value for measuring transmission quality of the internet of vehicles information.
Channel parallelization may be a communication technique that allows data to be transmitted over multiple parallel channels at the same time to increase the rate and efficiency of data transmission.
For the embodiment of the disclosure, the variable matrix corresponding to the transmitting node, the first relay node, the edge node and the second relay node can be diagonalized through channel parallelization, so that the variable matrix is converted into the diagonal matrix, the diagonal matrix is the element non-zero on the main diagonal, and the non-main diagonal elements are all set to zero, so that the calculation is simplified, the calculation complexity is reduced, and the mean square error value of the information of the internet of vehicles meets the optimization target.
In summary, compared with the prior art, the method for processing the information of the internet of vehicles has the advantages that the information of the internet of vehicles transmitted through the system node and transmitted by the transmitting node is received, wherein the system node comprises a first relay node, an edge node and a second relay node; and diagonalizing variable matrixes corresponding to the transmitting node, the first relay node, the edge node and the second relay node through channel parallelization so that the mean square error value of the information of the internet of vehicles meets an optimization target, wherein the optimization target is that the mean square error value is smaller than a preset mean square error value. For the scheme of the disclosure, two relay nodes are utilized to combine with an edge node, so that large-range information transmission from a transmitting node to a receiving node is realized; in channel parallelization, by diagonalizing the variable matrix, calculation can be effectively simplified, and calculation complexity is reduced, so that calculation resource consumption is reduced.
Further, as a refinement and extension of the foregoing embodiment, in order to fully describe a specific implementation procedure of the method of the present embodiment, the present embodiment provides a specific method as shown in fig. 3, where the method includes the following steps:
Step 201, capturing signal energy in the internet of vehicles information transmission process through a wireless energy carrying technology, so as to convert the signal energy into electric energy, and charging batteries of the first relay node, the edge node, the second relay node and/or the receiving node.
Among other things, wireless energy-carrying (SWIPT) technology may allow for simultaneous transmission of information and energy during wireless communication to provide energy charging for terminal devices.
For the embodiment of the disclosure, due to limited volume, the terminal device (such as the first relay node, the edge node, the second relay node and/or the receiving node) is provided with limited battery capacity, which results in insufficient cruising ability and reduced user experience. The wireless energy-carrying (SWIPT) technology is introduced to realize the cooperative transmission of information and energy, so that the terminal equipment is charged with energy while the high-speed transmission of the information is ensured, the life cycle of a network is prolonged, the problem of energy shortage of a communication system is effectively solved, the stability of data transmission is ensured, and the reliability of system transmission is improved.
Specifically, an antenna or other sensor may be used to capture signal energy during the transmission of internet of vehicles information, such as RF (radio frequency) signals, wi-Fi signals, cellular network signals, etc., and convert the captured signal energy to electrical energy to charge the batteries of the first relay node, the edge node, the second relay node, and/or the receiving node.
Step 202, obtaining perfect channel state information; and based on perfect channel state information, eliminating self-interference in the process of transmitting the information of the internet of vehicles by the system node.
The channel state information may be information describing characteristics of a wireless channel, and may include parameters such as gain, phase, delay, etc. of the channel; the perfect channel state information may be complete information that the receiver can obtain from the channel between the sender and the receiver in an ideal case, and may include all the characteristics of the amplitude, phase, multipath effect, etc. of the channel.
Self-interference may be the interference that may occur between different antennas on the same transmitting node due to the use of multi-antenna technology in a wireless communication system, such interference being referred to as self-interference.
For the embodiments of the present disclosure, assuming that a perfect Channel State Information (CSI) is acquired by a user terminal (i.e., a receiving node) in a wireless communication system, self-interference generated due to multi-antenna transmission on a reverse propagation path may be eliminated at the corresponding node.
Then the signal received by the user S 1 can be expressed as:
Wherein y1 may represent the total signal received by user s 1; z 1＝G4F3G3Fr,n2,n1∈CN(0,IN) may represent gaussian white noise of the corresponding node, The normalized power superposition noise at user S 1 may be represented.
User S 2 takes the ratio β ε (0, 1) as an ID, which can be expressed as:
wherein Z 2＝H4F4H3Fr,n1,n4∈CN(0,IN) represents Gaussian white noise of the corresponding node, Representing the normalized power superimposed noise at user S 2, S 1,s2∈CM+1 represents the corresponding user transmit signal.
Then the energy collected at user S 2 needs to satisfy the constraint:
Where e represents the minimum amount of energy collected at user S 2.
And 203, diagonalizing variable matrixes corresponding to the transmitting node, the first relay node, the edge node and the second relay node through channel parallelization so that the mean square error value of the internet of vehicles information meets the optimization target.
The variable matrix may include, among other things, a beamforming matrix, a channel matrix, and the like.
In a wireless communication system, beamforming may be a technique of controlling the direction and shape of a beam by adjusting the phase and amplitude of an antenna array; in this way, the system may increase the power of the signal in a particular direction while reducing interference or noise in other directions, thereby improving the transmission quality and communication rate of the signal. The beamforming matrix may be a mathematical tool for this purpose, the beamforming matrix defining the phases and amplitudes that should be applied on each antenna element.
Channel matrices, also known as channel matrices or transmission matrices, describe the propagation characteristics of signals in a wireless channel, reflecting the transmission of signals from a transmitting antenna to a receiving antenna, and may contain multipath, fading, noise, etc.
For the embodiment of the present disclosure, diagonalizing, by channel parallelization, a variable matrix corresponding to a transmitting node, a first relay node, an edge node, and a second relay node, so that a mean square error value of internet of vehicles information satisfies an optimization target, which specifically may include:
Decoupling the optimization objective into a plurality of different optimization sub-objectives;
Based on a channel matching principle, diagonalizing variable matrixes of different optimization sub-targets, and converting the different optimization sub-targets into scalar forms;
Converting different optimization sub-targets into target-amount convex targets by using a variable substitution method, and obtaining target solutions corresponding to the target-amount convex targets;
And alternately iterating the target solutions to enable the mean square error value of the vehicle networking information to meet the optimization target.
In this embodiment, by decoupling the optimization problem (i.e., optimization objective) into a plurality of smaller, mutually independent optimization sub-problems (i.e., optimization sub-objectives); aiming at different optimization sub-problems, a diagonalization-based beamforming optimization method is adopted, a diagonalization matrix is formed in a channel parallelization mode, the beamforming matrix can be optimally converted into the optimization of the diagonal matrix, the optimization problem is simplified into a power distribution problem, and solutions of different optimization sub-problems are obtained; and finally, alternately iterating the obtained solutions of different optimization sub-problems to obtain the solution of the optimization problem (namely the optimization target).
Specifically, as shown in fig. 4, the optimization problem construction module may establish a mean square error value minimization problem based on the constructed bidirectional multi-hop communication system model in the edge cloud scene under the constraint of power and energy collection, so as to perform joint optimization on the beamforming matrix at the terminal device and the relay. From the signal received by the receiving node (user S 1,S2), the mean square error value at the receiving node can be expressed as:
J1＝Ε[||W1y1-s2||2]
J2＝Ε[||W2y2-s1||2] (4)
Where W 1,W2∈CN×N represents the linear receiver at the receiving node (user S 1,S2), respectively.
The optimization problem of minimizing the total mean square error value can be expressed as:
Since W i (i=1, 2) is independent of all constraints, the principle of wiener filtering can be used to obtain an optimum Order of the gameThe method can obtain:
Wherein,
The obtained optimal valueSubstituting the optimization problem (5) to reconstruct the optimization problem.
As shown in fig. 4, the algorithm solving module mainly includes a problem decoupling sub-module, a diagonalization sub-module, a variable substitution sub-module, and an alternate iteration sub-module.
The decoupling submodule is used for decoupling the beam forming optimization problem into different optimization subproblems based on the constructed mean square error value minimization problem;
The diagonalization submodule is used for diagonalizing the optimization variables of different optimization subproblems based on a channel matching principle, specifically, the problem of minimizing the mean square error value can be established based on a constructed system model, and the channel matrix can be diagonalized by utilizing a singular value decomposition technology; the beamforming matrix of a transmitting node (e.g., user S 1 or user S 2) may be diagonalized using the idea of channel parallelization based on channel matching.
Accordingly, the optimization variable shaping matrix of the optimization problem may be reduced to a diagonal matrix using the diagonal matrix to convert the optimization problem to scalar form.
The variable substitution sub-module may convert the optimization sub-problem to a simple scalar convex problem using variable substitution.
The alternate iteration sub-module can alternate and iterate solutions of different optimization sub-problems to obtain a solution of a final original optimization problem, and the beam forming optimization of the bidirectional multi-hop communication system under the edge cloud scene is completed, so that the calculation complexity can be effectively reduced.
Compared with the complexity of the SCA optimization scheme, the calculation complexity of the diagonalization algorithm scheme is reduced.
In summary, compared with the prior art, the method for processing the information of the internet of vehicles has the advantages that the information of the internet of vehicles transmitted through the system node and transmitted by the transmitting node is received, wherein the system node comprises a first relay node, an edge node and a second relay node; and diagonalizing variable matrixes corresponding to the transmitting node, the first relay node, the edge node and the second relay node through channel parallelization so that the mean square error value of the information of the internet of vehicles meets an optimization target, wherein the optimization target is that the mean square error value is smaller than a preset mean square error value. For the scheme of the disclosure, two relay nodes are utilized to combine with an edge node, so that large-range information transmission from a transmitting node to a receiving node is realized; in channel parallelization, by diagonalizing the variable matrix, calculation can be effectively simplified, and calculation complexity is reduced, so that calculation resource consumption is reduced.
The foregoing embodiment is a process of processing information of internet of vehicles described on the receiving node side, and further, for fully explaining implementation of this embodiment, this embodiment further provides another method of processing information of internet of vehicles, which may be applied to the transmitting node side for execution. As shown in fig. 5, the method includes:
Step 301, transmitting the internet of vehicles information transmitted by the system node to the receiving node, so as to perform diagonalization processing on variable matrixes corresponding to the transmitting node, the first relay node, the edge node and the second relay node of the system node through channel parallelization, so that the mean square error value of the internet of vehicles information meets the optimization target.
The receiving node can be a vehicle or road side device and the like responsible for receiving and processing the data from the transmitting node in the internet of vehicles system; the optimization target is that the mean square error value is smaller than a preset mean square error value, and the system node comprises a first relay node, an edge node and a second relay node.
For the embodiment of the disclosure, in the process that the transmitting node transmits the internet of vehicles information transmitted through the system node to the receiving node, as shown in fig. 2, a one-time complete communication process of the dual-hop relay system is a process that two source communication nodes (i.e., the user S1 and the user S2) both receive signals sent by opposite source, and according to the time spent for one-time complete communication, the dual-hop relay system can be divided into a four-time-slot bidirectional relay system, a three-time-slot bidirectional relay system and a two-time-slot bidirectional relay system. The two-slot relay system may be called a multicast broadcast double-hop relay system, and its transmission is divided into two phases, a multicast phase and a broadcast phase.
In the first time slot, i.e. the multiple access stage, two source nodes send signals to the first relay node and the second relay node (i.e. relay R1 and relay R2) at the same time, where the transmit power constraint of the source nodes is:
the transmit power constraints of the first relay node and the second relay node (i.e., relay R1 and relay R2) may be expressed as:
Wherein H 1,G1∈CM×N is the channel matrix of S 1 to R 1 and S 2 to R 2, respectively, F S1,FS2,F1,F2,∈CN×M is the beamforming matrix of S 1,S2,R1 and R 2, respectively, and p 1,p2 is the corresponding power constraint.
The power constraint of the edge node R c is expressed as:
Wherein F r∈CN×M is an edge node beamforming matrix, p r is maximum transmit power,
In the second time slot, the broadcast phase, the transmit power constraint of R 1,R2 is:
Wherein H 3,G3∈CM×N is the channel matrix of R c to R 1 and R c to R 2, and F 3,F4∈CN×M is the beam forming matrix of the second time slot of R 1 and R 2 ,X1＝G3FrG2F2,X2＝H3FrH2F1.
Specifically, trace operation is performed based on a beam forming matrix of the transmitting node, so that the total transmitting power of the transmitting node is smaller than or equal to a preset power threshold;
Performing trace operation based on the beam forming matrix of the first relay node and a channel matrix between the first relay node and the transmitting node, and/or performing trace operation based on the beam forming matrix of the first relay node and the channel matrix between the first relay node and the edge node, so that the total transmitting power of the first relay node is smaller than or equal to a preset power threshold;
performing trace operation based on a beam forming matrix of the edge node and a channel matrix between the edge node and the transmitting node so that the total transmitting power of the edge node is smaller than or equal to a preset power threshold;
And performing trace operation based on the beam forming matrix of the second relay node and a channel matrix between the second relay node and the transmitting node, and/or performing trace operation based on the beam forming matrix of the second relay node and the channel matrix between the second relay node and the edge node, so that the total transmitting power of the second relay node is smaller than or equal to a preset power threshold.
In summary, compared with the prior art, the method for processing the information of the internet of vehicles has the advantages that the information of the internet of vehicles transmitted through the system node and transmitted by the transmitting node is received, wherein the system node comprises a first relay node, an edge node and a second relay node; and diagonalizing variable matrixes corresponding to the transmitting node, the first relay node, the edge node and the second relay node through channel parallelization so that the mean square error value of the information of the internet of vehicles meets an optimization target, wherein the optimization target is that the mean square error value is smaller than a preset mean square error value. For the scheme of the disclosure, two relay nodes are utilized to combine with an edge node, so that large-range information transmission from a transmitting node to a receiving node is realized; in channel parallelization, by diagonalizing the variable matrix, calculation can be effectively simplified, and calculation complexity is reduced, so that calculation resource consumption is reduced.
In summary, compared with the prior art, the method for processing the information of the internet of vehicles has the advantages that the information of the internet of vehicles transmitted through the system node and transmitted by the transmitting node is received, wherein the system node comprises a first relay node, an edge node and a second relay node; and diagonalizing variable matrixes corresponding to the transmitting node, the first relay node, the edge node and the second relay node through channel parallelization so that the mean square error value of the information of the internet of vehicles meets an optimization target, wherein the optimization target is that the mean square error value is smaller than a preset mean square error value. For the scheme of the disclosure, two relay nodes are utilized to combine with an edge node, so that large-range information transmission from a transmitting node to a receiving node is realized; in channel parallelization, by diagonalizing the variable matrix, calculation can be effectively simplified, and calculation complexity is reduced, so that calculation resource consumption is reduced.
Based on the specific implementation of the methods shown in fig. 1 and fig. 3, the disclosure provides an information processing apparatus for internet of vehicles, as shown in fig. 6, the apparatus includes: a receiving module 31 and a processing module 32;
The receiving module 31 is configured to receive the internet of vehicles information transmitted by the transmitting node through the system node, where the system node includes a first relay node, an edge node, and a second relay node;
And the processing module 32 is configured to diagonalize variable matrices corresponding to the transmitting node, the first relay node, the edge node, and the second relay node through channel parallelization, so that a mean square error value of the internet of vehicles information meets an optimization target, where the optimization target is that the mean square error value is smaller than a preset mean square error value.
In a specific application scenario, as shown in fig. 6, the apparatus further includes: a capture module 33;
The capturing module 33 is configured to capture signal energy in the internet of vehicles information transmission process by using a wireless energy carrying technology, so as to convert the signal energy into electric energy, and charge the battery of the first relay node, the edge node, the second relay node and/or the receiving node.
In a specific application scenario, as shown in fig. 6, the apparatus further includes: an acquisition module 34, a cancellation module 35;
an acquisition module 34, configured to acquire perfect channel state information;
And the eliminating module 35 is configured to eliminate self-interference in the process of transmitting the internet of vehicles information by the system node based on the perfect channel state information.
In a specific application scenario, the processing module 32 may be configured to decouple the optimization objective into a plurality of different optimization sub-objectives;
Based on a channel matching principle, diagonalizing variable matrixes of different optimization sub-targets, and converting the different optimization sub-targets into scalar forms, wherein the variable matrixes comprise beam forming matrixes and channel matrixes;
Converting different optimization sub-targets into scalar convex targets by using a variable substitution method, and obtaining target solutions corresponding to the scalar convex targets;
and alternately iterating the target solutions to enable the mean square error value of the internet of vehicles information to meet an optimization target.
It should be noted that, other corresponding descriptions of each functional unit related to the internet of vehicles information processing device provided by the present disclosure may refer to corresponding descriptions in fig. 1 and fig. 3, and are not repeated herein.
Further, as a specific implementation of the method shown in fig. 5, the embodiment provides an information processing apparatus of internet of vehicles applicable to a transmitting node side, as shown in fig. 7, the apparatus includes: a transmitting module 41;
The transmitting module 41 is configured to transmit, to a receiving node, the internet of vehicles information transmitted through a system node, so as to diagonalize, by using channel parallelization, a variable matrix corresponding to the transmitting node, a first relay node, an edge node and a second relay node of the system node, so that a mean square error value of the internet of vehicles information meets an optimization target, where the optimization target is that the mean square error value is smaller than a preset mean square error value, and the system node includes the first relay node, the edge node and the second relay node.
In a specific application scenario, as shown in fig. 7, the apparatus further includes: a first operation module 42, a second operation module 43, a third operation module 44, and a fourth operation module 45;
A first operation module 42, configured to perform trace operation based on a beamforming matrix of a transmitting node, so that a total transmitting power of the transmitting node is less than or equal to a preset power threshold;
A second operation module 43, configured to perform trace operation based on the beamforming matrix of the first relay node and a channel matrix between the first relay node and a transmitting node, and/or perform trace operation based on the beamforming matrix of the first relay node and a channel matrix between the first relay node and an edge node, so that the total transmitting power of the first relay node is less than or equal to a preset power threshold;
A third operation module 44, configured to perform trace operation based on the beamforming matrix of the edge node and the channel matrix between the edge node and the transmitting node, so that the total transmitting power of the edge node is less than or equal to a preset power threshold;
And a fourth operation module 45, configured to perform trace operation based on the beamforming matrix of the second relay node and the channel matrix between the second relay node and the transmitting node, and/or perform trace operation based on the beamforming matrix of the second relay node and the channel matrix between the second relay node and the edge node, so that the total transmitting power of the second relay node is less than or equal to a preset power threshold.
It should be noted that, other corresponding descriptions of each functional unit related to the internet of vehicles information processing device provided by the present disclosure may refer to corresponding descriptions in fig. 5, and are not described herein again.
Based on the above-described methods shown in fig. 1, 3 and 5, accordingly, the present disclosure also provides a computer-readable storage medium having a computer program stored thereon, which when executed by a processor, implements the above-described methods shown in fig. 1, 3 and 5.
Based on such understanding, the technical solution of the present disclosure may be embodied in the form of a software product, which may be stored in a non-volatile storage medium (may be a CD-ROM, a U-disk, a mobile hard disk, etc.), and includes several instructions for causing a computer device (may be a personal computer, a server, or a network device, etc.) to execute the method of each implementation scenario of the present disclosure.
Based on the methods shown in fig. 1, 3 and 5 and the virtual device embodiments shown in fig. 6 and 7, in order to achieve the above objects, the disclosed embodiments further provide an electronic device that may be configured on an end side of a vehicle (such as an electric automobile), where the device includes a storage medium and a processor; a storage medium storing a computer program; a processor for executing a computer program to implement the methods as described above and shown in fig. 1, 3 and 5.
Optionally, the physical device may further include a user interface, a network interface, a camera, radio frequency (RadioFrequency, RF) circuitry, sensors, audio circuitry, WI-FI modules, and so on. The user interface may include a Display screen (Display), an input unit such as a Keyboard (Keyboard), etc., and the optional user interface may also include a USB interface, a card reader interface, etc. The network interface may optionally include a standard wired interface, a wireless interface (e.g., WI-FI interface), etc.
It will be appreciated by those skilled in the art that the above-described physical device structure provided by the present disclosure is not limiting of the physical device, and may include more or fewer components, or may combine certain components, or a different arrangement of components.
The storage medium may also include an operating system, a network communication module. The operating system is a program that manages the physical device hardware and software resources described above, supporting the execution of information handling programs and other software and/or programs. The network communication module is used for realizing communication among all components in the storage medium and communication with other hardware and software in the information processing entity equipment.
From the above description of embodiments, it will be apparent to those skilled in the art that the present disclosure may be implemented by means of software plus necessary general hardware platforms, or may be implemented by hardware. According to the method, the device and the electronic equipment for processing the information of the Internet of vehicles, compared with the prior art, the method and the device for processing the information of the Internet of vehicles are disclosed, wherein the information of the Internet of vehicles is transmitted through the system node by receiving the transmission node, and the system node comprises a first relay node, an edge node and a second relay node; and diagonalizing variable matrixes corresponding to the transmitting node, the first relay node, the edge node and the second relay node through channel parallelization so that the mean square error value of the information of the internet of vehicles meets an optimization target, wherein the optimization target is that the mean square error value is smaller than a preset mean square error value. For the scheme of the disclosure, two relay nodes are utilized to combine with an edge node, so that large-range information transmission from a transmitting node to a receiving node is realized; in channel parallelization, by diagonalizing the variable matrix, calculation can be effectively simplified, and calculation complexity is reduced, so that calculation resource consumption is reduced.
It should be noted that in this document, relational terms such as "first" and "second" and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises an element.
The above is merely a specific embodiment of the disclosure to enable one skilled in the art to understand or practice the disclosure. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the disclosure. Thus, the present disclosure is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (10)
1. An information processing method of internet of vehicles, which is applied to a receiving node side for execution, the method comprising:
Receiving the internet of vehicles information transmitted by the transmitting node through the system node, wherein the system node comprises a first relay node, an edge node and a second relay node;
And diagonalizing the variable matrixes corresponding to the transmitting node, the first relay node, the edge node and the second relay node through channel parallelization so that the mean square error value of the Internet of vehicles information meets an optimization target, wherein the optimization target is that the mean square error value is smaller than a preset mean square error value.
2. The method according to claim 1, wherein the method further comprises:
And capturing signal energy in the information transmission process of the Internet of vehicles through a wireless energy carrying technology, so as to convert the signal energy into electric energy and charge batteries of the first relay node, the edge node, the second relay node and/or the receiving node.
3. The method according to claim 1, wherein the method further comprises:
acquiring perfect channel state information;
And eliminating self-interference in the process of transmitting the internet of vehicles information by the system node based on the perfect channel state information.
4. The method according to claim 1, wherein the diagonalizing the variable matrices corresponding to the transmitting node, the first relay node, the edge node, and the second relay node through channel parallelization so that a mean square error value of the internet of vehicles information meets an optimization target includes:
Decoupling the optimization objective into a plurality of different optimization sub-objectives;
Based on a channel matching principle, diagonalizing variable matrixes of different optimization sub-targets, and converting the different optimization sub-targets into scalar forms, wherein the variable matrixes comprise beam forming matrixes and channel matrixes;
Converting different optimization sub-targets into scalar convex targets by using a variable substitution method, and obtaining target solutions corresponding to the scalar convex targets;
and alternately iterating the target solutions to enable the mean square error value of the internet of vehicles information to meet an optimization target.
5. An information processing method of internet of vehicles, which is characterized by being applied to a transmitting node side for execution, the method comprising:
and transmitting the internet of vehicles information transmitted by the system node to a receiving node, and diagonalizing the variable matrixes corresponding to the transmitting node, the first relay node, the edge node and the second relay node of the system node through channel parallelization to enable the mean square error value of the internet of vehicles information to meet an optimization target, wherein the optimization target is that the mean square error value is smaller than a preset mean square error value, and the system node comprises the first relay node, the edge node and the second relay node.
6. The method according to claim 4, wherein the method further comprises:
performing trace operation based on a beam forming matrix of a transmitting node so that the total transmitting power of the transmitting node is smaller than or equal to a preset power threshold;
Performing trace operation based on the beam forming matrix of the first relay node and a channel matrix between the first relay node and a transmitting node, and/or performing trace operation based on the beam forming matrix of the first relay node and a channel matrix between the first relay node and an edge node, so that the total transmitting power of the first relay node is smaller than or equal to a preset power threshold;
Performing trace operation based on the beam forming matrix of the edge node and a channel matrix between the edge node and a transmitting node so that the total transmitting power of the edge node is smaller than or equal to a preset power threshold;
and performing trace operation based on the beam forming matrix of the second relay node and a channel matrix between the second relay node and a transmitting node, and/or performing trace operation based on the beam forming matrix of the second relay node and the channel matrix between the second relay node and an edge node, so that the total transmitting power of the second relay node is smaller than or equal to a preset power threshold.
7. An information processing device of internet of vehicles, which is applied to a receiving node side, the device comprises:
The system comprises a receiving module, a transmitting module and a receiving module, wherein the receiving module is used for receiving the internet-of-vehicles information transmitted by a transmitting node through a system node, and the system node comprises a first relay node, an edge node and a second relay node;
and the processing module is used for diagonalizing the variable matrixes corresponding to the transmitting node, the first relay node, the edge node and the second relay node through channel parallelization so as to enable the mean square error value of the internet of vehicles information to meet an optimization target, wherein the optimization target is that the mean square error value is smaller than a preset mean square error value.
8. An information processing device of internet of vehicles, which is applied to a transmitting node side, the device comprises:
The system comprises a transmitting module, a receiving module and a receiving module, wherein the transmitting module is used for transmitting the internet of vehicles information transmitted by a system node to the receiving node, so that the variable matrixes corresponding to the transmitting node, a first relay node, an edge node and a second relay node of the system node are diagonalized through channel parallelization, and the mean square error value of the internet of vehicles information meets an optimization target, the optimization target is that the mean square error value is smaller than a preset mean square error value, and the system node comprises the first relay node, the edge node and the second relay node.
9. An electronic device, comprising:
At least one processor; and
A memory communicatively coupled to the at least one processor; wherein,
The memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-4 or the method of any one of claims 5-6.
10. A computer program product comprising a computer program which, when executed by a processor, implements the method according to any one of claims 1-4 or the method according to any one of claims 5-6.
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