CN117858105B - Multi-unmanned aerial vehicle cooperation set dividing and deploying method in complex electromagnetic environment - Google Patents
Multi-unmanned aerial vehicle cooperation set dividing and deploying method in complex electromagnetic environment Download PDFInfo
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Abstract
The invention provides a multi-unmanned aerial vehicle cooperation set dividing and deploying method in a complex electromagnetic environment, belonging to the technical field of wireless communication; the method comprises the following steps: s1, constructing a system model, and designing and calculating a collaborative deployment scheme; s2, initializing the position coordinates of the multiple unmanned aerial vehicles by adopting a K-means++ clustering algorithm according to the initial position of the user; s3, primarily dividing the collaboration set of the multiple unmanned aerial vehicles to obtain an initial collaboration set; s4, calculating the weight of the initial collaboration set, and selecting a non-overlapping final collaboration set through weight size sorting to serve as a division result; s5, fixing user tags in the final collaboration set, clustering again by adopting the same clustering algorithm in a cyclic traversal mode, updating the position coordinates of more unmanned aerial vehicles, and completing deployment; the invention can ensure that all users receive good signals as far as possible in a complex electromagnetic environment, obviously improves the signal-to-interference-and-noise ratio of the users subject to external interference and provides stable and reliable communication service.
Description
Technical Field
The invention belongs to the technical field of wireless communication, and relates to a multi-unmanned aerial vehicle collaborative set division and deployment method in a complex electromagnetic environment, which is applied to the process of collaborative set division and three-dimensional position deployment of unmanned aerial vehicle clusters according to the position condition of interfered users.
Background
The unmanned aerial vehicle has advantages of mobility, stability, wide coverage and the like, can dynamically and rapidly adjust the position of the unmanned aerial vehicle, and provides reliable communication service for the terminal through a multipoint cooperative transmission mode, so that the unmanned aerial vehicle is widely applied to the military and civil fields. However, due to the broadcasting characteristics and the direct-view link characteristics of the unmanned aerial vehicle wireless transmission, the transmission information is easy to be subjected to malicious electromagnetic interference, and the information transmission safety is seriously damaged; the external complex electromagnetic interference and the interference between the terminals of different channels in the interior are key factors for restricting the increase of the air-ground communication capacity of the wide-area coverage unmanned aerial vehicle under the frequency multiplexing architecture.
At present, the unmanned aerial vehicle has the characteristics of small volume and small equipment, and can carry less resources, and once the unmanned aerial vehicle is interfered by external indiscriminate full-frequency strong power, the unmanned aerial vehicle cannot make complex processing technologies like a ground base station, such as spread spectrum and frequency hopping technologies, so as to resist relevant interference. Therefore, through mutual cooperation of a plurality of unmanned aerial vehicles, the interference-to-noise ratio of received signals of the interfered nodes is enhanced, the communication quality is improved, and the communication reliability can be ensured. The division of the collaboration set is an important factor affecting the communication quality, however, the existing collaboration technology only carries out related researches on a fixed base station mode, and the collaboration deployment scheme among unmanned aerial vehicles with dynamic characteristics is not considered yet.
The prior art has introduced multi-frame directional antenna unmanned aerial vehicle as wireless base station, provides the effective deployment scheme of coverage for ground users, has provided the best 3D deployment mode of multi-frame unmanned aerial vehicle, solves the problem of the maximum downlink coverage performance with minimum transmitting power. The prior art also introduces a distributed multi-point cooperative transmission method, which can be close to the performance of the centralized multi-point cooperative transmission and has the advantage of high calculation efficiency.
The prior art discloses a UQPSK data link system for small and medium unmanned aerial vehicles, which can improve the anti-interference performance of the unmanned aerial vehicle and ground communication and improve the reliability of data transmission; however, the technology performs relatively complex signal processing on the unmanned aerial vehicle, so that more power is wasted, and the due advantages of the unmanned aerial vehicle are reduced. From all the prior art introduced by the disclosure, only the fixed base station is focused, and related schemes of the cooperation set division based on the mobility of the unmanned aerial vehicle and the position deployment of the unmanned aerial vehicle are lack of research, which also correspondingly becomes the research key points of the technicians in the field.
Disclosure of Invention
Based on the current situation in the background technology, the invention aims to solve the problem of how to resist external malicious interference when the unmanned aerial vehicle cluster is used as a base station to communicate with ground users; the invention can ensure and obviously improve the signal-to-interference-and-noise ratio of the users with external interference under the complex electromagnetic environment, and establishes a collaborative set division and unmanned aerial vehicle cluster position deployment scheme based on the severely interfered users aiming at all the users.
The invention adopts the following technical scheme to achieve the purpose:
a multi-unmanned aerial vehicle cooperation set dividing and deploying method in a complex electromagnetic environment comprises the following steps:
S1, constructing a system model, and carrying out scheme design and calculation of collaborative deployment among multiple unmanned aerial vehicle base stations with dynamic characteristics according to the system model;
s2, initializing the position coordinates of the multiple unmanned aerial vehicles by adopting a K-means++ clustering algorithm according to the initial positions of all users in the system model;
s3, primarily dividing the collaboration set of the multiple unmanned aerial vehicles according to the positions of the interfered users in the system model in a mode of setting a distance threshold value to obtain multiple initial collaboration sets;
S4, calculating the weight of each initial collaboration set, and selecting a non-overlapping final collaboration set as a multi-unmanned aerial vehicle collaboration set division result in a weight ranking mode;
S5, fixing user labels in the final collaboration set according to the division result of the multi-unmanned aerial vehicle collaboration set, adopting a K-means++ clustering algorithm again, completing the clustering process in a cyclic traversal mode, updating the position coordinates of the multi-unmanned aerial vehicle, and completing the position deployment of the multi-unmanned aerial vehicle.
Further, in step S1, when a system model is constructed, basic parameters of the unmanned aerial vehicle and basic parameters of the user in the system model are determined, and after the determination is completed, all unmanned aerial vehicles adopt transmitting signals with the same frequency, and a channel communicated between the unmanned aerial vehicle and the user is a rayleigh channel; after channel attenuation between the unmanned aerial vehicle and the corresponding user is determined, the construction of a system model is completed.
Further, in step S2, initializing the position coordinates of the multiple unmanned aerial vehicle includes the following steps:
S21, adopting a K-means++ clustering algorithm to select an initial clustering center;
s22, carrying out a clustering process, initializing the two-dimensional position of a clustering center, and calculating the height of the clustering center;
s23, after expanding the clustering center to a three-dimensional space, carrying out the clustering process in the same step S22 again, and updating the two-dimensional position coordinates and the height coordinates of the clustering center;
S24, updating the clustering label of the user into a corresponding clustering center through a repeated cyclic clustering process; and stopping circulation when the clustering label is not changed along with updating, wherein the current clustering center is the three-dimensional position coordinate of the corresponding unmanned aerial vehicle, otherwise, returning to the step S23 to perform the clustering process again.
Further, in step S3, the collaborative set is divided for the interfered user, the interfered user is randomly selected, the unmanned aerial vehicle serving the user is recorded, and two adjacent unmanned aerial vehicles are adopted to form the initial collaborative set corresponding to the user.
Further, in step S4, in the determined multiple initial collaboration sets, users with the same initial collaboration set are classified into a category, so as to obtain all initial collaboration sets in a non-overlapping state of the unmanned aerial vehicle, and users corresponding to the initial collaboration sets;
Selecting a final collaboration set in a non-overlapping state of the unmanned aerial vehicle; the weight of each classified initial collaboration set is calculated, and after sorting is carried out according to the weights, the initial collaboration sets are sequentially selected from big to small; and after any collaboration set is selected, discarding the rest collaboration sets containing unmanned aerial vehicles in the collaboration set, thereby obtaining a multi-unmanned aerial vehicle collaboration set division result.
Further, in step S5, firstly, a cluster label of the cluster center and the user in step S2 is obtained, then, according to the multi-unmanned aerial vehicle cooperation set dividing result in step S4, the coordinate value of the cluster center is updated once, and then, circulation is performed to perform the clustering process;
In the cyclic clustering process, each user is traversed firstly, and if the current user is a collaboration set user, skipping is performed; otherwise, traversing the cluster centers, calculating the distance between the current user and each cluster center, selecting the cluster center closest to the current user, and classifying the current user into the class of the cluster center; and updating the triaxial coordinate values of the clustering centers again at the moment, if the corresponding clustering labels are unchanged, the three-dimensional position coordinates of the current clustering centers are the three-dimensional position coordinates of the corresponding unmanned aerial vehicles, and otherwise, repeating the cyclic clustering process.
In summary, by adopting the technical scheme, the invention has the following beneficial effects:
The method can dynamically adjust the collaborative set dividing scheme of the unmanned aerial vehicle cluster according to the position change and the interference condition change of the users, thereby ensuring that all the users can receive good signals as far as possible. By applying the method, the signal-to-interference-and-noise ratio of the users subjected to external interference can be remarkably improved in a complex electromagnetic environment, a multi-unmanned aerial vehicle cooperation set dividing and deploying scheme aiming at all the users is smoothly established, and stable and reliable communication service is provided.
Drawings
FIG. 1 is a schematic diagram of a system model constructed in the method of the present invention;
FIG. 2 is a schematic diagram of a location of a randomly initialized user in an embodiment of the present invention;
FIG. 3 is a graph of clustered positions of the unmanned aerial vehicle in the example of the present invention;
FIG. 4 is a schematic diagram of a collaboration result after the final collaboration set is partitioned in the embodiment of the present invention;
Fig. 5 is a schematic diagram showing a change of a signal-to-interference-and-noise ratio of a user 4 along with a transmitting power of an unmanned aerial vehicle in an example of the present invention;
FIG. 6 is a schematic view of a position of three unmanned aerial vehicles before collaboration in another example;
fig. 7 is a schematic diagram of a collaboration result after two unmanned aerial vehicles are adopted to collaborate in another example;
fig. 8 is a schematic diagram of a collaboration result after three unmanned aerial vehicles are adopted for collaboration in another example;
Fig. 9 is a schematic diagram of a change in the signal-to-interference-and-noise ratio of the user 1 with the transmit power of the drone in another example.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is apparent that the described embodiments are some embodiments of the present invention, but not all embodiments of the present invention. The components of the embodiments of the present invention generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations.
Thus, the following detailed description of the embodiments of the invention, as presented in the figures, is not intended to limit the scope of the invention, as claimed, but is merely representative of selected embodiments of the invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Examples
A multi-unmanned aerial vehicle cooperation set dividing and deploying method in a complex electromagnetic environment is provided, and the detailed content of each step in the method will be described in detail by a specific example.
Step one: system model correlation
Firstly, parameters of a system model, such as unmanned plane basic parameters and user basic parameters, need to be determined; in the present embodiment, it is common toThe unmanned aerial vehicle is/>The first user provides communication service and will be/>The unmanned aerial vehicle is denoted/>，The position of the unmanned plane is marked as/>Can be written as/>Form three-axis coordinates.
Will be the firstThe individual users are denoted/>，/>The position of the user is marked/>Can be written specifically asForm three-axis coordinates. Will serve the first/>The unmanned aerial vehicle set of individual users is denoted/>In the embodiment, the situation that two unmanned aerial vehicles cooperatively serve the same user is mainly considered, and the service of the first/>The/>, of individual userThe unmanned aerial vehicle is denoted/>; The unmanned aerial vehicle set may be/>Wherein/>Can be empty, when/>When empty, one can/>Is marked as/>。
In the system model, each user carries a single antenna, and the number of the antennas carried by each unmanned aerial vehicle isThe 6 antennas are arranged in a uniform linear array or a uniform planar array mode, and the uniform linear array is adopted in the embodiment. Coverage angle/>, of each unmanned aerial vehicleOnly at the coverage angle/>The communication service provided by the corresponding unmanned aerial vehicle can be obtained by the users in the range.
In this embodiment, gaussian white noise powerThe task area for providing communication service by multiple unmanned aerial vehicles is side length/>Is a square area of (a); unmanned aerial vehicle flying height/>The range is as follows: ; the number of users subject to external interference is/> Name, received interference power is denoted/>. The overall structure and composition of the system model can be seen in the schematic of fig. 1.
In the system model, after the basic parameters of the unmanned aerial vehicle and the basic parameters of the user are determined, all unmanned aerial vehicles adopt the same-frequency transmitting signals and adopt a symbol-level precoding mode, so that the interference among users can be avoided, the interference power can be utilized, and the signal-to-interference-and-noise ratio is further increased. In this embodiment, the carrier frequency of the transmission signal isBandwidth of; The total power of the single-frame unmanned aerial vehicle is/>. In addition, in this embodiment, the channel for communication between the drone and the user is a rayleigh channel.
Will be the firstUnmanned aerial vehicle/>The total number of users of the service is recorded as/>Subject to the/>Unmanned aerial vehicle/>Service/>The individual users are denoted/>Position coordinates are/>。
In this embodiment, the transmission symbol of the unmanned aerial vehicle adopts MPSK modulation technique; will be the firstThe signal vector transmitted at the transmitting antenna port of the unmanned aerial vehicle is expressed as/>，/>，/>Representing a channel matrix,/>Represents the/>The number of antennas carried by the unmanned aerial vehicle is 1, and 1 represents a single antenna carried by a user.
Will be the firstFrame unmanned aerial vehicle and service's/>Individual user/>The distance between them is denoted/>The channel fading per unit distance is denoted/>Then/>Frame unmanned aerial vehicle and service's/>Individual user/>Channel fading/>, betweenThe formula is as follows:
Will be the first Communication channel/>, between a drone and its covered usersExpressed by the following formula:
Wherein the matrix Is a diagonal matrix,/>，/>Representing a real number array; matrix/>Represents a large scale fade, as follows:
In the method, in the process of the invention, Representative matrix/>Middle/>Diagonal elements,/>Representative matrix/>The last diagonal element in (a); matrix/>Matrix/>The elements in (a) follow Rayleigh distribution and represent small-scale fading, and/>The individual user receives the/>Received signal of unmanned aerial vehicleThe formula is as follows:
In the method, in the process of the invention, Is Gaussian white noise; /(I)，/>Representative/>Obeying Gaussian distribution, the mean value is 0, and the variance is/>。
Fig. 2 shows a position indication of a randomly initialized user, which can be synchronously referred to after the following steps, such as the entering step, for the example of the present embodiment.
Step two: initializing the position of the unmanned aerial vehicle by adopting a clustering algorithm
According to the initial position of the user, a K-means++ clustering algorithm is adopted to initialize the position of the unmanned aerial vehicle, and the method specifically comprises the following steps:
(1) Initial cluster center selection: and selecting an initial cluster center by adopting a K-means++ cluster algorithm.
Corresponding to the sum ofUnmanned aerial vehicle of frame is selected/> fromsample point one by oneThe probability that a sample point farther from the rest of the cluster centers is selected as the next cluster center is higher for each cluster center in the following manner:
(1-1) randomly selecting one user from the uniformly distributed users as a first initial cluster center, the position of which is marked as ；
(1-2) Calculating the shortest distance between each user and the currently existing cluster center, and recording as; If there is currently/>And (3) clustering centers: i.e. cluster center set/>Then/>Individual users and/>Distance set of each cluster center/>Is expressed as follows:
Then For the shortest distance therein, namely:
Calculating the probability that each user is selected as the next cluster center The following formula:
The set of probabilities to be calculated The method is characterized by comprising the following steps:
In the method, in the process of the invention, Representing a natural number set; /(I)Represents the/>Position coordinates of individual users and cluster center set/>The position coordinates of any cluster centers are different;
Selecting a collection The sample point corresponding to the maximum probability value in the cluster is used as the next cluster center, and the position coordinate/>, corresponding to the new cluster centerExpressed as:
(1-3) repeating the step (1-2) until a total is selected And clustering centers.
(2) Initializing a two-dimensional position of a clustering center: for the firstUnmanned aerial vehicle, if/>Position coordinates of individual user/>And/>Position coordinates of individual cluster centers/>Distance/>Shortest, the following formula:
In the method, in the process of the invention, ; Grouping the user to the cluster center, i.e., serving the user's/>Position coordinates of unmanned aerial vehicle/>Change the position coordinates/>, of the cluster center；
(3) Calculating the cluster center height: calculate the firstDistance maximum value/>, of each cluster center and users classified into the cluster centerThe following formula:
Thus, the first is calculated Height coordinates of individual cluster centers/>The following formula:
(4) After expanding to the three-dimensional space, clustering is carried out for one time: here, step (2) is the same.
(5) Updating a cluster centerAxis coordinates/>And/>Axis coordinates/>Updating the corresponding coordinate value to be the average value of all elements in the clustering center, wherein the average value is represented by the following formula:
(6) Updating a cluster center Axis coordinates/>Given by the calculation method in step (3), the following formula:
Whereby the update completes the first Three-dimensional position coordinates of the cluster centers are as follows:
(7) Circulation stop condition: after the updating is finished, if the clustering label is not changed, the current clustering center is the three-dimensional position coordinate corresponding to the unmanned aerial vehicle, namely the first Coordinates of the unmanned aerial vehicle/>; If the clustering label changes along with the updating of the coordinates, repeating the clustering process of the steps (4), 5 and 6) and updating the coordinates, and checking whether the corresponding clustering label changes.
In this embodiment, three-dimensional initial position and coordinate data of the clustered unmanned aerial vehicle are shown in table 1 below after initialization.
TABLE 1 three-dimensional initial position and coordinate data schematic table of unmanned aerial vehicle
The data in the table represent the coordinates of 3 unmanned aerial vehicles in the embodiment, and the corresponding position schematic diagram is shown in fig. 3.
Step three: partitioning an initial collaboration set for interfered users
In this embodiment, the collaborative set is divided for the interfered users, and the interfered users are randomly selected and recorded asThe unmanned aerial vehicle serving the user is noted as/>Two unmanned aerial vehicle are adopted to form a collaboration set;
according to the interfered users Position coordinates/>Calculate and remove unmanned aerial vehicle/>The outer two unmanned aerial vehicles with the nearest distances are respectively marked as adjacent unmanned aerial vehicles/>And/>Its corresponding coordinates are/>And/>Interfered user/>And adjacent unmanned plane/>And/>The distance between them corresponds to/>And/>The following formula:
because the unmanned aerial vehicle can move, different from the ground base station, the characteristics of the adjacent cells or the adjacent base stations can be easily determined, the embodiment sets a distance threshold value If interfered user/>Adjacent unmanned plane/>Or/>The distance between them is less than the distance threshold/>Unmanned aerial vehicle/>, serving the userCan be connected with adjacent unmanned plane/>Or (b)An initial collaboration set is composed, for example: when/>When correspond to the collection/>I.e. an initial collaboration set, i.e. the unmanned set is denoted (here, th/>The named user is the interfered user/>）：
When (when)When correspond to the collection/>The initial collaboration set cannot be constructed, i.e., the unmanned aerial vehicle set is noted as:
Table 2 below gives an example of the initial collaboration set in this embodiment, see.
Table 2 various sequence number tables in initial collaboration set
Step four: selecting non-overlapping final collaboration sets
After a plurality of initial collaboration sets are determined in the third mode, users with the same initial collaboration set are classified into one type, and all initial collaboration sets in the unmanned aerial vehicle non-overlapping state and corresponding users in the collaboration sets are obtained.
Then selecting a final collaboration set in a non-overlapping state of the unmanned aerial vehicle; the weight of each classified initial collaboration set is calculated, and after sorting is carried out according to the weights, the initial collaboration sets are sequentially selected from big to small; after any collaboration set is selected, discarding the rest collaboration sets containing unmanned aerial vehicles in the collaboration set, thereby obtaining a multi-unmanned aerial vehicle collaboration set division result;
the weight calculation mode of the collaboration set is as follows: if the collaboration set contains Individual user, where/>The collaboration set of individual users is，/>Representing ordinal number of adjacent unmanned plane,/>，/>; Then the weight of the collaboration set/>Expressed as:
In the method, in the process of the invention, For/>Individual user to adjacent drone/>Distance between them.
Under the data of this embodiment, the selected final collaboration set and the corresponding weights are shown in table 3 below.
TABLE 3 various sequence numbers and weight tables in final collaboration set
Step five: clustering is conducted again according to the multi-unmanned aerial vehicle collaboration set division result
In this embodiment, on the basis of completion of K-means++ clustering, the clustering labels of the users in the collaboration set are fixed, and the K-means++ clustering process is performed again, specifically as follows:
(1) Acquiring an initial clustering center and a clustering label: this part is obtained in step two.
(2) Changing the clustering label of the user: changing the clustering labels of the users in the collaborative set according to the multi-unmanned-aerial-vehicle collaborative set dividing result in the step four, so that the clustering labels simultaneously contain labels of two unmanned aerial vehicles in the collaborative set;
(3) Updating a cluster center 、/>Coordinates: because some labels are added in the step (2), the clustering center needs to be recalculated, and the/>, of the clustering center is updated、/>The coordinates are the average value of all elements in the class, and the updating method is the same as the updating method in the step (5).
(4) Updating a cluster centerCoordinates: calculating the maximum value/>, of the distance between the clustering center and the users in the classThe height of the clustering center is obtained, and the calculation and updating method is the same as that in the step (3).
(5) And (5) entering a circulation for clustering: firstly traversing each user, and skipping if the current user is a collaboration set user; otherwise, traversing the cluster centers, calculating the distance between the current user and each cluster center, selecting the cluster center closest to the current user, and classifying the current user into the class of the cluster center, wherein the method is the same as that in the step (4).
(6) Updating cluster centers again、/>The coordinates are the average value of all elements in the class, and the updating method is the same as the updating method in the step (5).
(7) Re-computing and updating cluster centersThe coordinate, calculation and updating method is the same as the (3) in the second step.
(8) If the corresponding clustering label is unchanged, the current clustering center is the three-dimensional position coordinate of the corresponding unmanned aerial vehicle, the division of the collaboration set and the deployment of the unmanned aerial vehicle position are completed, and the method process is ended; otherwise, repeating the steps (5) (6) (7) of the fifth step until the cluster labels are unchanged.
Fig. 4 shows a schematic diagram of a collaboration result after the final collaboration set is divided under the data of the present embodiment, which can be synchronously referred to; table 4 below is a final three-dimensional position coordinate table for 3 unmanned aerial vehicles.
Table 4 final three-dimensional position coordinate table for unmanned aerial vehicle
The following is a description of the comparison process and the effect display of the signal-to-interference and noise ratio of the user before and after the implementation of the method of the embodiment, that is, before and after the division of the collaboration set.
Before and after the collaboration set is divided, the comparison mode of the signal to interference and noise ratio of the user is as follows:
the interference received by each user includes: other drone interference, local other user interference, gaussian white noise, and possibly malicious interference. In the method of the embodiment, the interference of other unmanned aerial vehicles can be reduced as much as possible by dividing the collaboration set, and the interference of other local users can be eliminated and utilized by symbol-level precoding to resist malicious interference.
Assume that the transmitting power of the user served by each unmanned aerial vehicle is the total power of the userInterference between users does not exist, and only fading of path loss to transmission power is considered; gaussian white noise Power/>The interference power received by the interfered user is/>Unmanned aerial vehicle transmit power/>. First/>The collaboration set of individual users is，/>，/>; The signal-to-interference-and-noise ratio calculation formula is as follows:
In the method, in the process of the invention, Representation of unmanned plane/>With user/>Channel between,/>Indicating whether malicious interference exists, namely the malicious interference does not exist when the value is 0, and exists when the value is 1.
The calculation formula of the signal-to-interference-and-noise ratio of the users outside the collaboration set is as follows:
the signal-to-interference-and-noise ratio of each user before and after the collaborative set partitioning is shown in table 5 below.
TABLE 5 comparison schematic table of signal-to-interference-and-noise ratio (dB) before and after collaborative set partitioning
When the transmitting power of the unmanned aerial vehicle is changed, the signal-to-interference-and-noise ratio of the user with the sequence number of 4 is changed as shown in figure 5.
From the above data and the result graph, after the collaborative set division, the signal-to-interference-plus-noise ratio of the interfered users 4 and 5 is increased, and the signal-to-interference-plus-noise ratio of other normal users still keeps a higher degree.
After the collaboration set is divided, the unmanned aerial vehicle can move towards the direction where the interfered user is located, and meanwhile, in order to ensure that the original user is continuously served, the flying height of the unmanned aerial vehicle can be increased.
The distance between the undisturbed users and the unmanned aerial vehicle can be increased, so the signal-to-interference-plus-noise ratio of the users can be reduced, but the signal-to-interference-plus-noise ratio of the normal users is in a higher value, so the users can still keep normal communication after sacrificing some signal-to-interference-plus-noise ratios.
The signal-to-interference-and-noise ratio of the interfered users is not obviously improved by simply adopting a power distribution mode, so that a symbol-level precoding mode can be adopted to utilize the interference among the users on the basis of the division of the cooperation set, thereby obviously improving the signal-to-interference-and-noise ratio of the interfered users.
In the application of the method of the embodiment, three unmanned aerial vehicles can be used for cooperating the user positions, the distribution of the users and the unmanned aerial vehicles before cooperation is shown in fig. 6, and the user with the serial number 1 is the interfered user.
Based on the distribution positions of fig. 6, if two unmanned aerial vehicles are adopted to cooperate, the deployment result of the unmanned aerial vehicles after cooperation is shown in fig. 7; however, in the three-unmanned-plane cooperation mode, the corresponding unmanned-plane deployment result after cooperation is shown in fig. 8, and the signal-to-interference-and-noise ratio of each user before and after the cooperation set division is shown in the following table 6.
TABLE 6 Signal-to-interference-and-noise ratio (dB) comparison schematic table before and after cooperation set division under three unmanned aerial vehicles cooperation
When the transmitting power of the unmanned aerial vehicle is changed, the signal-to-interference-and-noise ratio change of the user with the sequence number of 1 in fig. 8 is shown in fig. 9. Therefore, when the three unmanned aerial vehicles cooperate, the signal-to-interference-and-noise ratio of the interfered user 1 is greatly improved, and the method of the embodiment ensures that all users receive good signals as much as possible.
Claims (7)
1. A multi-unmanned aerial vehicle cooperation set dividing and deploying method in a complex electromagnetic environment is characterized by comprising the following steps:
S1, constructing a system model, and carrying out scheme design and calculation of collaborative deployment among multiple unmanned aerial vehicle base stations with dynamic characteristics according to the system model;
s2, initializing the position coordinates of the multiple unmanned aerial vehicles by adopting a K-means++ clustering algorithm according to the initial positions of all users in the system model;
s3, primarily dividing the collaboration set of the multiple unmanned aerial vehicles according to the positions of the interfered users in the system model in a mode of setting a distance threshold value to obtain multiple initial collaboration sets;
S4, calculating the weight of each initial collaboration set, and selecting a non-overlapping final collaboration set as a multi-unmanned aerial vehicle collaboration set division result in a weight ranking mode;
S5, fixing user labels in the final collaboration set according to the division result of the multi-unmanned aerial vehicle collaboration set, adopting a K-means++ clustering algorithm again, completing a clustering process in a cyclic traversal mode, updating the position coordinates of the multi-unmanned aerial vehicle, and completing the position deployment of the multi-unmanned aerial vehicle;
in step S1, when a system model is constructed, basic parameters of the unmanned aerial vehicle and basic parameters of the user in the system model are determined in the following manner:
Sharing of The unmanned aerial vehicle is/>The first user provides communication service and will be/>The unmanned aerial vehicle is denoted/>The position of the unmanned plane is marked as/>; Will/>The individual users are denoted/>The position of the user is marked/>; Will serve the first/>The unmanned aerial vehicle set of individual users is denoted/>Unmanned aerial vehicle set/>In, service No./>The/>, of individual userThe unmanned aerial vehicle is denoted/>；
In the system model, each user carries a single antenna, and the number of the antennas carried by each unmanned aerial vehicle isRoot, and/>The root antennas are distributed in a uniform linear array or a uniform planar array mode; the coverage angle of each unmanned aerial vehicle is recorded as/>Only at the coverage angle/>A user in the range can obtain the communication service provided by the corresponding unmanned aerial vehicle; determining a task area for providing communication services by multiple unmanned aerial vehicles as a side length/>Is a square area of (a); let unmanned aerial vehicle fly height be/>And determine/>Upper limit of value of/>And lower limit of; The number of users subject to external interference is recorded as/>The interference power to which it is subjected is denoted/>；
After the basic parameters of the unmanned aerial vehicle and the basic parameters of the user are determined, all unmanned aerial vehicles adopt the same-frequency transmitting signals, and the carrier frequency of the transmitting signals is recorded asThe bandwidth is noted as/>; The total power of a single unmanned aerial vehicle is recorded as/>And the channel for communication between the unmanned aerial vehicle and the user is a Rayleigh channel;
Will be the first Unmanned aerial vehicle/>The total number of users of the service is recorded as/>Subject to the/>Unmanned aerial vehicle/>Service/>The individual users are represented asPosition coordinates are/>；
Will be the firstThe signal vector transmitted at the transmitting antenna port of the unmanned aerial vehicle is expressed as/>，/>，/>Representing a channel matrix,/>Represents the/>The number of antennas carried by the unmanned aerial vehicle is 1, and 1 represents a single antenna carried by a user; finally, determining channel fading between the unmanned aerial vehicle and the corresponding user, thereby completing the construction of a system model;
Will be the first Frame unmanned aerial vehicle and service's/>Individual user/>The distance between them is denoted/>The channel fading per unit distance is denoted/>Then/>Frame unmanned aerial vehicle and service's/>Individual user/>Channel fading/>, betweenThe formula is as follows:
Will be the first Communication channel/>, between a drone and its covered usersExpressed by the following formula:
Wherein the matrix Is a diagonal matrix,/>，/>Representing a real number array; matrix/>Representing large scale fading, written as:
In the method, in the process of the invention, Representative matrix/>Middle/>Diagonal elements,/>Representative matrix/>The last diagonal element in (a); matrix arrayMatrix/>The elements in (a) follow Rayleigh distribution and represent small-scale fading, and/>The individual user receives the/>Received signal of unmanned aerial vehicleThe formula is as follows:
In the method, in the process of the invention, Is white gaussian noise.
2. The method for partitioning and deploying a multi-unmanned aerial vehicle collaboration set in a complex electromagnetic environment according to claim 1, wherein the method is characterized by comprising the following steps: in step S2, initializing the position coordinates of the multiple unmanned aerial vehicle, including the following steps:
S21, adopting a K-means++ clustering algorithm to select an initial clustering center;
s22, carrying out a clustering process, initializing the two-dimensional position of a clustering center, and calculating the height of the clustering center;
s23, after expanding the clustering center to a three-dimensional space, carrying out the clustering process in the same step S22 again, and updating the two-dimensional position coordinates and the height coordinates of the clustering center;
S24, updating the clustering label of the user into a corresponding clustering center through a repeated cyclic clustering process; and stopping circulation when the clustering label is not changed along with updating, wherein the current clustering center is the three-dimensional position coordinate of the corresponding unmanned aerial vehicle, otherwise, returning to the step S23 to perform the clustering process again.
3. The method for partitioning and deploying a multi-unmanned aerial vehicle collaboration set in a complex electromagnetic environment according to claim 2, wherein the method is characterized by comprising the following steps: in step S21, corresponding to the sumUnmanned aerial vehicle of frame is selected/> fromsample point one by oneThe probability that a sample point farther from the rest of the cluster centers is selected as the next cluster center is higher for each cluster center in the following manner:
S211, randomly selecting one user from uniformly distributed users as a first initial clustering center when no clustering center exists, wherein the position and the sitting mark are as follows ；
S212, calculating the shortest distance between each user and the current existing cluster center, and marking as; If there is currently/>And (3) clustering centers: i.e. cluster center set/>Then/>Individual users and/>Distance set of each cluster center/>Is expressed as follows:
Then For the shortest distance therein, namely:
Calculating the probability that each user is selected as the next cluster center The following formula:
after the calculation is completed, a set of corresponding probabilities is obtained ; Select collection/>The sample point corresponding to the maximum probability value in the cluster is used as the next cluster center, so that the position coordinate/>, corresponding to the new cluster center, is obtained；
S213, repeating the step S212 until the sum is selectedAnd clustering centers.
4. The method for partitioning and deploying a multi-unmanned aerial vehicle collaboration set in a complex electromagnetic environment according to claim 3, wherein the method comprises the following steps: in step S22, for the firstUnmanned aerial vehicle, if/>Position coordinates of individual user/>And/>Position coordinates of individual cluster centers/>Distance/>Shortest, the following formula:
In the method, in the process of the invention, ; Grouping the user to the cluster center, i.e., serving the user's/>Position coordinates of unmanned aerial vehicle/>Change the position coordinates/>, of the cluster center；
Subsequently, calculate the firstDistance maximum value/>, of each cluster center and users classified into the cluster centerThe following formula:
Thus, the first is calculated Height coordinates of individual cluster centers/>The following formula:
In step S23, after expanding to the three-dimensional space to cluster again, updating the primary clustering center Axis coordinates/>And/>Axis coordinates/>Updating the corresponding coordinate value to be the average value of all elements in the clustering center, wherein the average value is represented by the following formula:
updating a cluster center Axis coordinates/>The following formula:
Whereby the update completes the first Three-dimensional position coordinates of the cluster centers are as follows:
after the updating is finished, if the clustering label is not changed, the three-dimensional position coordinate of the current clustering center is the three-dimensional position coordinate of the corresponding unmanned plane, namely the first Coordinates of the unmanned aerial vehicle/>; If the cluster label changes with the update of the coordinates, returning to the step S23 to perform the clustering process again and update the coordinates, and checking whether the corresponding cluster label changes.
5. The method for partitioning and deploying a multi-unmanned aerial vehicle collaboration set in a complex electromagnetic environment according to claim 4, wherein the method is characterized by comprising the following steps: in step S3, the cooperation set is divided for the interfered users, and the interfered users are randomly selected and recorded asThe unmanned aerial vehicle serving the user is noted as/>Two unmanned aerial vehicle are adopted to form a collaboration set;
according to the interfered users Position coordinates/>Calculate and remove unmanned aerial vehicle/>The outer two unmanned aerial vehicles with the nearest distances are respectively marked as adjacent unmanned aerial vehicles/>And/>Its corresponding coordinates are/>And/>Interfered user/>With adjacent unmanned aerial vehicleAnd/>The distance between them corresponds to/>And/>The following formula:
Setting a distance threshold If interfered user/>Adjacent unmanned plane/>Or/>The distance between them is less than the distance threshold/>Unmanned aerial vehicle/>, serving the userCan be connected with adjacent unmanned plane/>Or/>An initial collaboration set is formed, otherwise, the initial collaboration set cannot be formed; in this way a plurality of initial collaboration sets are determined.
6. The method for partitioning and deploying multi-unmanned aerial vehicle cooperation set in a complex electromagnetic environment according to claim 5, wherein the method is characterized by comprising the following steps: in step S4, classifying users with the same initial collaboration set into one type in the determined multiple initial collaboration sets to obtain all initial collaboration sets in a non-overlapping state of the unmanned aerial vehicle and corresponding users in the collaboration sets;
Selecting a final collaboration set in a non-overlapping state of the unmanned aerial vehicle; the weight of each classified initial collaboration set is calculated, and after sorting is carried out according to the weights, the initial collaboration sets are sequentially selected from big to small; after any collaboration set is selected, discarding the rest collaboration sets containing unmanned aerial vehicles in the collaboration set, thereby obtaining a multi-unmanned aerial vehicle collaboration set division result;
the weight calculation mode of the collaboration set is as follows: if the collaboration set contains Individual user, where/>The collaboration set of individual users is，/>Representing ordinal number of adjacent unmanned plane,/>，/>; Then the weight of the collaboration set/>Expressed as:
In the method, in the process of the invention, For/>Individual user to adjacent drone/>Distance between them.
7. The method for partitioning and deploying a multi-unmanned aerial vehicle collaboration set in a complex electromagnetic environment according to claim 6, wherein the method is characterized by comprising the following steps: in step S5, firstly, acquiring cluster labels of a cluster center and a user in step S2, and then changing the cluster labels of the users in the collaborative set according to the multi-unmanned aerial vehicle collaborative set division result in step S4, so that the cluster labels simultaneously contain labels of two unmanned aerial vehicles in the collaborative set;
Then, in the same manner as in step S23, the primary cluster center is updated 、/>、/>Axis coordinates, will/>、/>Updating the axis coordinate value to be the average value of all elements in the class, and calculating the maximum value/>, of the distance between the clustering center and the users in the classObtaining the height/>, of the cluster centerThereby updating/>An axis coordinate value;
Entering a loop to perform a clustering process, firstly traversing each user, and skipping if the current user is a collaboration set user; otherwise, traversing the cluster centers, calculating the distance between the current user and each cluster center, selecting the cluster center closest to the current user, and classifying the current user into the class of the cluster center; at this point the cluster center is updated again 、/>、/>And (5) the axis coordinate value, if the corresponding clustering label is not changed, the three-dimensional position coordinate of the current clustering center is the three-dimensional position coordinate of the corresponding unmanned aerial vehicle, and otherwise, the cyclic clustering process is repeated.
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