CN113993175B - Unmanned aerial vehicle communication switching method, system, equipment and storage medium - Google Patents

Unmanned aerial vehicle communication switching method, system, equipment and storage medium Download PDF

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Publication number
CN113993175B
CN113993175B CN202111243723.0A CN202111243723A CN113993175B CN 113993175 B CN113993175 B CN 113993175B CN 202111243723 A CN202111243723 A CN 202111243723A CN 113993175 B CN113993175 B CN 113993175B
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unmanned aerial
aerial vehicle
switching
qoe
parameters
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CN113993175A (en
Inventor
武青
任鑫
李小翔
王�华
王恩民
刘溟江
姚中原
钱开荣
牛晨辉
周国栋
张宇
马强
王有超
祝金涛
吴昊
吕亮
朱俊杰
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Huaneng Clean Energy Research Institute
Clean Energy Branch of Huaneng International Power Jiangsu Energy Development Co Ltd Clean Energy Branch
Huaneng International Power Jiangsu Energy Development Co Ltd
Shengdong Rudong Offshore Wind Power Co Ltd
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Huaneng Clean Energy Research Institute
Clean Energy Branch of Huaneng International Power Jiangsu Energy Development Co Ltd Clean Energy Branch
Huaneng International Power Jiangsu Energy Development Co Ltd
Shengdong Rudong Offshore Wind Power Co Ltd
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W36/00—Hand-off or reselection arrangements
    • H04W36/08—Reselecting an access point
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W36/00—Hand-off or reselection arrangements
    • H04W36/24—Reselection being triggered by specific parameters
    • H04W36/30—Reselection being triggered by specific parameters by measured or perceived connection quality data
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W36/00—Hand-off or reselection arrangements
    • H04W36/24—Reselection being triggered by specific parameters
    • H04W36/32—Reselection being triggered by specific parameters by location or mobility data, e.g. speed data

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  • Engineering & Computer Science (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Signal Processing (AREA)
  • Mobile Radio Communication Systems (AREA)

Abstract

The invention discloses a communication switching method, a system, equipment and a storage medium of an unmanned aerial vehicle, wherein S1, switching parameters are determined according to the position and the speed of the unmanned aerial vehicle; s2, adjusting a switching parameter by using a nonlinear index DPSO algorithm; s3, judging whether the adjusted switching parameters meet QoE of unmanned aerial vehicle video transmission; if not, turning to S2, if yes, taking the adjusted switching parameter as the current communication switching parameter of the unmanned aerial vehicle and taking the switching parameter as the initial value of the next nonlinear index DPSO algorithm. The video transmission QoE index is met, video transmission efficiency during inspection of the unmanned aerial vehicle is improved, and inspection efficiency of the unmanned aerial vehicle is improved.

Description

Unmanned aerial vehicle communication switching method, system, equipment and storage medium
Technical Field
The invention belongs to the field of wireless communication, and relates to an unmanned aerial vehicle communication switching method, system, equipment and storage medium.
Background
The offshore wind farm has wide range, complex environment, difficult access, difficult traffic equipment selection and great obstruction to maintenance of operation and maintenance personnel. At present, operation and maintenance personnel often adopt unmanned aerial vehicle inspection and other modes to carry out operation and maintenance detection of the fan. The unmanned aerial vehicle has very high requirements on communication bandwidth when carrying out video inspection, and because the wind power plant fans have large distances, the unmanned aerial vehicle flies far away when carrying out the inspection, and therefore, the unmanned aerial vehicle needs to switch communication links when carrying out communication. In the traditional communication switching process, the video communication quality of the unmanned aerial vehicle cannot be guaranteed, so that the inspection efficiency of the unmanned aerial vehicle is reduced.
Disclosure of Invention
The invention aims to overcome the defects of the prior art, and provides an unmanned aerial vehicle communication switching method, system, equipment and storage medium, which meet video transmission QoE indexes, improve video transmission efficiency during inspection of an unmanned aerial vehicle and improve inspection efficiency of the unmanned aerial vehicle.
In order to achieve the purpose, the invention is realized by adopting the following technical scheme:
the unmanned aerial vehicle communication switching method comprises the following steps:
s1, determining a switching parameter according to the position and the speed of the unmanned aerial vehicle;
s2, adjusting a switching parameter by using a nonlinear index DPSO algorithm;
s3, judging whether the adjusted switching parameters meet QoE of unmanned aerial vehicle video transmission; if not, turning to S2, if yes, taking the adjusted switching parameter as the current communication switching parameter of the unmanned aerial vehicle and taking the switching parameter as the initial value of the next nonlinear index DPSO algorithm.
Preferably, the specific process of S2 is:
s21, updating the position and speed of the unmanned aerial vehicle, and calculating QoE of video transmission of the unmanned aerial vehicle under different parameters;
s22, dynamically adjusting acceleration and weight factors through iteration;
s23, recording the optimal value of a single unmanned aerial vehicle and the global optimal value of all unmanned aerial vehicles in each iteration.
Further, the formula for updating the position and speed of the unmanned aerial vehicle is:
v i ＝ω·v i +c 1 ·rabd(0,1)·(p i -x i )+c 2 ·rand(0,1)·(p g -x i )
wherein p is i For the switching parameter, p corresponding to the ith unmanned aerial vehicle when meeting the optimal video QoE g And (5) switching parameters corresponding to the condition that the unmanned aerial vehicle in all wind power plants meets the video QoE. rabd (0, 1) is a random number within 0-1, ω is a weight factor, c 1 And c 2 Acceleration is the same.
Still further, c 1 And c 2 The iterative calculation process of (1) is as follows:
where iter is the current iteration number and iter_max is the maximum iteration number.
Still further, the iterative calculation process of the weight factor ω is:
where iter is the current iteration number and iter_max is the maximum iteration number.
Preferably, the calculation process of the QoE of the video transmission is:
QoE video ＝4.23-0.0672T init -0.742F rebuf -0.106T rebuf
wherein T is init 、T rebuf And F rebuf The initial play-out delay, the average rebuffering time and the rebuffering frequency, respectively.
A drone communication switching system, comprising:
the switching parameter determining unit is used for determining switching parameters according to the position and the speed of the unmanned aerial vehicle;
a switching parameter adjusting unit for adjusting the switching parameter using a nonlinear exponential DPSO algorithm;
the switching parameter judging application unit is used for judging whether the adjusted switching parameter meets QoE of unmanned aerial vehicle video transmission or not; if not, turning to S2, if yes, taking the adjusted switching parameter as the current communication switching parameter of the unmanned aerial vehicle and taking the switching parameter as the initial value of the next nonlinear index DPSO algorithm.
A computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, the processor implementing the steps of the unmanned aerial vehicle communication switching method of any of the preceding claims when the computer program is executed.
A computer readable storage medium storing a computer program which when executed by a processor performs the steps of the unmanned aerial vehicle communication switching method of any one of the preceding claims.
Compared with the prior art, the invention has the following beneficial effects:
the invention uses DPSO algorithm to switch network of unmanned aerial vehicle, the purpose of the algorithm is: in the flight process of the unmanned aerial vehicle, a group of combination parameters with the highest QoE optimization value for video transmission of the unmanned aerial vehicle is selected in a certain time according to a plurality of parameters in the flight process, including the combination of the flight speed, acceleration, position, base station parameters and the like of the unmanned aerial vehicle. Finally, the unmanned aerial vehicle meets the video transmission QoE requirement in the whole inspection process, the video transmission efficiency during inspection of the unmanned aerial vehicle is improved, and the inspection efficiency of the unmanned aerial vehicle is improved.
Drawings
FIG. 1 is a schematic view of an unmanned aerial vehicle inspection of an offshore wind farm of the present invention;
FIG. 2 is a schematic diagram of a fan external wireless network coverage of the present invention;
FIG. 3 is a flow chart of a handover algorithm according to the present invention;
FIG. 4 is a schematic diagram of a hardware architecture of a switching algorithm according to the present invention;
fig. 5 is a schematic diagram of an electronic structure of the present invention.
Detailed Description
The invention is described in further detail below with reference to the attached drawing figures:
as shown in fig. 1, the present invention first builds a wireless coverage facility at an offshore wind farm. Because offshore wind farm keeps away from the coast, ordinary public base station can't cover offshore wind farm, consequently every offshore wind farm can build independent looped netowrk and connect every fan to booster station, as shown in fig. 2, and independent fan looped netowrk only is used for transmitting the fan signal, and unmanned aerial vehicle can't insert wherein patrolling and examining. Aiming at the scene that the unmanned aerial vehicle flies in the wind power plant, an AP device is deployed outside the fan, each AP is subjected to physical marking, and the wind power plant ring network is accessed through the switch, so that the coverage of the offshore wind power plant is completed.
The unmanned aerial vehicle is in the wind-powered electricity generation field inspection in-process, and service unmanned aerial vehicle's AP can constantly change, consequently in the in-process that changes, need carry out the switching of AP, have very big influence to unmanned aerial vehicle video transmission's QoE in this in-process.
And (3) deploying an AP device outside each fan by utilizing the fan ring network already deployed in the offshore wind farm, accessing the fan ring network by the AP device through a switch, and marking each AP. The fan looped netowrk gathers in the booster station, and the control of all APs in the looped netowrk is accomplished to the AC controller of booster station department to this wireless network that accomplishes whole wind-powered electricity generation field covers.
As shown in fig. 3, the communication switching method of the offshore wind power inspection unmanned aerial vehicle specifically comprises the following steps:
network initial parameters are determined according to the industrial parameters of each AP in the wind farm network. The QoE (Quality of Experience ) model was determined as follows:
QoE video ＝4.23-0.0672T init -0.742F rebuf -0.106T rebuf
wherein T is init ,T rebuf ,F rebuf Representing the initial play-out delay, average rebuffering time and rebuffering frequency, respectively.
The switching parameters are adjusted by using a nonlinear exponential DPSO (Discrete Particle Swarm Optimization Algorithm, discrete particle swarm optimization) algorithm to perform switching actions. The specific principle is as follows:
firstly, calculating video transmission QoE under flight parameters of a preceding unmanned aerial vehicle, and calculating T according to a video transmission sensor init ,T rebuf ,F rebuf 。
The DSPO algorithm adjusts unmanned aerial vehicle flight parameters including unmanned aerial vehicle flight speed, position, acceleration and the like. Wherein, unmanned aerial vehicle's p i The definition is as follows: the ith unmanned aerial vehicle is subjected to video QoE maximum value calculated by all switching parameters when the ith unmanned aerial vehicle is in the current iteration number.
The optimal value of the global unmanned aerial vehicle is defined as: all unmanned aerial vehicles pass through the video QoE maximum value calculated by all switching parameters when the unmanned aerial vehicle is in the current iteration number.
In the optimized setting, the position of the unmanned aerial vehicle is as follows:
x i ＝(x i1 ,…,x iM )
wherein x is i1 ,…,x iM Is the position of the unmanned aerial vehicle in the 1 st to M th moments.
The speed of the unmanned aerial vehicle is as follows:
v i ＝(v i1 ,…,v iM )
wherein v is i1 ,…,v iM Is the speed of the unmanned aerial vehicle in the 1 st to the M th moments.
Updating the position and speed of the unmanned aerial vehicle by using a DPSO algorithm, and recording QoE of unmanned aerial vehicle video transmission of each iteration:
v i ＝ω·v i +c 1 ·rand(0,1)·(p i -x i )+c 2 ·rand(0,1)
x′ i ＝x i +x i
rand (0, 1) is a random number taken within 0-1. Omega is the inertia weight, and the invention provides a formula for dynamically changing and adjusting omega along with the iteration times:
where iter is the current iteration number and iter_max is the maximum iteration number.
c 1 ，c 2 The acceleration is the ratio of the unmanned plane to the global optimal direction and the self optimal direction, and the invention provides the formulas for calculating c1 and c2
Where iter is the current iteration number and iter_max is the maximum iteration number.
The video transmission QoE is a mode for evaluating and scoring, the video transmission QoE is classified into 5 grades from high to low, the evaluation result of the video to be evaluated, which is not perceived in the lossless or video damage degree, is excellent, and 5 grades can be obtained; the video to be evaluated with less serious damage degree and perceptible evaluation result is good, and can be obtained by 4 points; the video to be evaluated with slight damage is generally evaluated, and can be obtained for 3 points; the video to be evaluated with serious video damage degree has worse evaluation result, and can be obtained by 2 points; the video to be evaluated with very serious video damage degree has a poor evaluation result, and can be obtained by 1 score. Therefore, if the QoE of the inspection video of the unmanned plane is to be satisfied, qoeveimo should be 3 or more.
Judging whether QoE of unmanned plane video transmission after switching parameters are adjusted is more than or equal to 3; if not, turning to S2, if yes, taking the adjusted switching parameter as the current communication switching parameter of the unmanned aerial vehicle and taking the switching parameter as the initial value of the next nonlinear index DPSO algorithm.
In order to ensure QoE lifting and balance of the unmanned aerial vehicle, the DPSO switching algorithm adjusts switching parameters every 10 seconds during movement of the unmanned aerial vehicle. And taking the adjusted switching parameters as initial values of the next DPSO algorithm, and calculating QoE under different switching parameters by the DPSO algorithm according to the position and the speed of the unmanned aerial vehicle at the moment through a video QoE model. The DPSO algorithm dynamically adjusts the flight speed and acceleration of the unmanned aerial vehicle according to the iteration times, finally obtains the highest QoE of the unmanned aerial vehicle within 10 seconds, determines the switching parameters of the unmanned aerial vehicle, and takes the obtained result as the initial value of the DPSO algorithm next time, and dynamically adjusts the switching parameters in the process of moving the user so as to ensure the QoE improvement and balance in the flight process of the unmanned aerial vehicle.
As shown in fig. 4, the switching algorithm hardware structure includes a network establishment module, an unmanned aerial vehicle video transmission module and an unmanned aerial vehicle inspection switching algorithm module which are sequentially connected.
As shown in fig. 5, the electronic device comprises a memory 50 for storing a computer program; a processor 51 for implementing the steps of the unmanned aerial vehicle switching communication method as mentioned in any of the above embodiments when executing a computer program. In some embodiments, the electronic device may further include a display 52, an input/output interface 53, a communication interface 34, or network interface, a power supply 55, and a communication bus 56. Among other things, the display 52, input output interface 53 such as a Keyboard (Keyboard) pertain to a user interface, which may optionally also include standard wired interfaces, wireless interfaces, etc.
The unmanned aerial vehicle communication switching system of the invention comprises:
and the switching parameter determining unit is used for determining the switching parameter according to the position and the speed of the unmanned aerial vehicle.
And the switching parameter adjusting unit is used for adjusting the switching parameters by using a nonlinear index DPSO algorithm.
The switching parameter judging application unit is used for judging whether the adjusted switching parameter meets QoE of unmanned aerial vehicle video transmission or not; if not, turning to S2, if yes, taking the adjusted switching parameter as the current communication switching parameter of the unmanned aerial vehicle and taking the switching parameter as the initial value of the next nonlinear index DPSO algorithm.
The computer equipment comprises a memory, a processor and a computer program stored in the memory and capable of running on the processor, wherein the processor realizes the steps of the unmanned aerial vehicle communication switching method when executing the computer program.
The computer readable storage medium of the present invention stores a computer program which, when executed by a processor, implements the steps of the unmanned aerial vehicle communication switching method.
The above is only for illustrating the technical idea of the present invention, and the protection scope of the present invention is not limited by this, and any modification made on the basis of the technical scheme according to the technical idea of the present invention falls within the protection scope of the claims of the present invention.

Claims (6)

1. The unmanned aerial vehicle communication switching method is characterized by comprising the following steps of:
s1, determining a switching parameter according to the position and the speed of the unmanned aerial vehicle;
s2, adjusting a switching parameter by using a nonlinear index DPSO algorithm;
the specific process is as follows:
s21, updating the position and speed of the unmanned aerial vehicle, and calculating QoE of video transmission of the unmanned aerial vehicle under different parameters;
the formula for updating the position and speed of the unmanned aerial vehicle is as follows:
wherein the method comprises the steps ofIs->Corresponding switching parameters when the personal unmanned aerial vehicle meets the optimal video QoE (quality of experience), and the switching parameters are->Corresponding switching parameters when the unmanned aerial vehicle in all wind power plants meets the video QoE; />For random number within 0-1, < >>Is the weightFactor (F)>Andacceleration is the same;
the calculation process of the QoE of video transmission is as follows:
wherein the method comprises the steps of、/>And->Respectively an initial play-out delay, an average rebuffering time and a rebuffering frequency
S22, dynamically adjusting acceleration and weight factors through iteration;
s23, recording the optimal value of a single unmanned aerial vehicle and the global optimal value of all unmanned aerial vehicles in each iteration;
s3, judging whether the adjusted switching parameters meet QoE of unmanned aerial vehicle video transmission; if not, turning to S2, if yes, taking the adjusted switching parameter as the current communication switching parameter of the unmanned aerial vehicle and taking the switching parameter as the initial value of the next nonlinear index DPSO algorithm.
2. The unmanned aerial vehicle communication switching method of claim 1, wherein,and->The iterative calculation process of (1) is as follows:
wherein the method comprises the steps ofFor the current iteration number, +.>Is the maximum number of iterations.
3. The unmanned aerial vehicle communication switching method of claim 1, wherein the weight factorThe iterative calculation process of (1) is as follows:
wherein the method comprises the steps ofFor the current iteration number, +.>Is the maximum number of iterations.
4. An unmanned aerial vehicle communication switching system, comprising:
the switching parameter determining unit is used for determining switching parameters according to the position and the speed of the unmanned aerial vehicle;
a switching parameter adjusting unit for adjusting the switching parameter using a nonlinear exponential DPSO algorithm;
the specific process is as follows:
s21, updating the position and speed of the unmanned aerial vehicle, and calculating QoE of video transmission of the unmanned aerial vehicle under different parameters;
the formula for updating the position and speed of the unmanned aerial vehicle is as follows:
wherein the method comprises the steps ofIs->Corresponding switching parameters when the personal unmanned aerial vehicle meets the optimal video QoE (quality of experience), and the switching parameters are->Corresponding switching parameters when the unmanned aerial vehicle in all wind power plants meets the video QoE; />For random number within 0-1, < >>As a weight factor, ++>Andacceleration is the same;
the calculation process of the QoE of video transmission is as follows:
wherein the method comprises the steps of、/>And->Respectively an initial play-out delay, an average rebuffering time and a rebuffering frequency
S22, dynamically adjusting acceleration and weight factors through iteration;
s23, recording the optimal value of a single unmanned aerial vehicle and the global optimal value of all unmanned aerial vehicles in each iteration;
the switching parameter judging application unit is used for judging whether the adjusted switching parameter meets QoE of unmanned aerial vehicle video transmission or not; if not, turning to S2, if yes, taking the adjusted switching parameter as the current communication switching parameter of the unmanned aerial vehicle and taking the switching parameter as the initial value of the next nonlinear index DPSO algorithm.
5. A computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that the processor, when executing the computer program, implements the steps of the unmanned aerial vehicle communication handover method of any of claims 1 to 3.
6. A computer readable storage medium storing a computer program, characterized in that the computer program when executed by a processor implements the steps of the unmanned aerial vehicle communication switching method of any of claims 1 to 3.
CN202111243723.0A 2021-10-25 2021-10-25 Unmanned aerial vehicle communication switching method, system, equipment and storage medium Active CN113993175B (en)

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Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103279793A (en) * 2013-04-25 2013-09-04 北京航空航天大学 Task allocation method for formation of unmanned aerial vehicles in certain environment
CN106990792A (en) * 2017-05-23 2017-07-28 西北工业大学 Mix the multiple no-manned plane collaboration sequential coupling task distribution method of gravitation search algorithm
CN110232492A (en) * 2019-04-01 2019-09-13 南京邮电大学 A kind of multiple no-manned plane cotasking dispatching method based on improvement discrete particle cluster algorithm
CN111884829A (en) * 2020-06-19 2020-11-03 西安电子科技大学 Method for maximizing multi-unmanned aerial vehicle architecture income

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103279793A (en) * 2013-04-25 2013-09-04 北京航空航天大学 Task allocation method for formation of unmanned aerial vehicles in certain environment
CN106990792A (en) * 2017-05-23 2017-07-28 西北工业大学 Mix the multiple no-manned plane collaboration sequential coupling task distribution method of gravitation search algorithm
CN110232492A (en) * 2019-04-01 2019-09-13 南京邮电大学 A kind of multiple no-manned plane cotasking dispatching method based on improvement discrete particle cluster algorithm
CN111884829A (en) * 2020-06-19 2020-11-03 西安电子科技大学 Method for maximizing multi-unmanned aerial vehicle architecture income

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