Coordinated Multipoint Transmission Method and System Based on Poisson-Delaunay Triangulation

Abstract

The present invention discloses a coordinated multi-point transmission method based on Poisson-Delaunay triangulation, comprising the following steps: constructing a spatial distribution model of unmanned aerial vehicle (UAV) base stations, and dividing the UAV set through Delaunay triangulation; calculating the minimum search radius within the search area of the UAVs, and determining the minimum search subset of the UAVs according to the UAV set; constructing a cooperation set based on the minimum search subset, and determining the cooperation UAV set of typical users according to the average received power of each cooperation set. The present invention also proposes a coordinated multi-point transmission system based on Poisson-Delaunay triangulation. The present invention solves the technical problems of high computational complexity and large resource occupancy of the existing transmission methods.

Description

Technical Field

[0001] The present invention relates to the field of communication technologies, and in particular, to a coordinated multi-point transmission method and system based on Poisson-Delaunay triangulation. Background Art

[0002] With the rapid development of wireless communication systems, coordinated multi-point transmission technology has attracted much attention as a key means to improve network capacity and coverage. However, existing coordinated multi-point transmission methods have a large computational overhead when searching for the collaboration set of users, which limits their application in actual networks. Traditional coordinated multi-point transmission methods often use heuristic algorithms based on distance or signal strength when searching for the user collaboration set, resulting in high computational complexity and large resource occupancy. The patent document with the application number 202311015465.X discloses a multi-UAV distributed control method based on a communication network under attack. By establishing a dynamic model of multiple UAVs, defining a directed communication topology structure of multiple UAVs, and obtaining the communication situation when the communication network between each UAV and its neighbor UAVs is under attack; based on the position information between each UAV and its neighbor UAVs, predicting the target positions of multiple UAVs under distributed control; using a method that combines an error dynamics system and a backstepping method with a filter to solve for the combined lift force and attitude controller input of the UAVs, and controlling the positions and attitudes of the UAVs based on a composite controller to achieve the convergence of position error and attitude error to 0, so as to achieve the distributed control objective. Therefore, there is an urgent need to propose a coordinated multi-point transmission method and system based on Poisson-Delaunay triangulation to solve the technical problems of high computational complexity and large resource occupancy of existing transmission methods. Summary of the Invention

[0003] The main object of the present invention is to propose a coordinated multi-point transmission method and system based on Poisson-Delaunay triangulation, aiming to solve the technical problems of high computational complexity and large resource occupancy of existing transmission methods.

[0004] To achieve the above object, the present invention provides a coordinated multi-point transmission method based on Poisson-Delaunay triangulation. Among them, the coordinated multi-point transmission method based on Poisson-Delaunay triangulation includes the following steps:

[0005] S1. Construct a spatial distribution model of UAV base stations, and divide the UAV set through Delaunay triangulation;

[0006] S2. Calculate the minimum search radius within the search area of the UAVs, and determine the minimum search subset of the UAVs according to the UAV set;

[0007] S3. Construct a collaboration set based on the minimum search subset, and determine the collaboration UAV set of typical users according to the average received power of each collaboration set.

[0008] One of the preferred solutions is that step S1 constructs a spatial distribution model of UAV base stations, specifically as follows:

[0009] All UAVs are distributed as a homogeneous Poisson point process with a density of λ0, equipped with M antennas, and hovering at the same height h; a typical user independent of the UAV distribution is located at the ground origin, i.e., O(0, 0, 0), equipped with a single antenna, and is served by N UAVs in the cooperation set.

[0010] One of the preferred solutions is that three UAVs in the cooperation set serve a typical user on the ground.

[0011] One of the preferred solutions is that step S1 divides the UAV set through Delaunay triangulation, specifically as follows: According to the spatial distribution model of UAV base stations, the Delaunay triangulation is constructed by the divide-and-conquer method, and based on each UAV vertex, the target area is triangulated using the Delaunay triangulation method to form a UAV set.

[0012] One of the preferred solutions is that the minimum search radius is:

[0013]

[0014] where R smin is the minimum search radius, and λ0 is the UAV density.

[0015] One of the preferred solutions is that step S3 is specifically as follows:

[0016] Obtain the distance d k (t) between the UAV at x k (t) at time t and the typical user, where 1 ≤ k ≤ m, and m is the total number of UAVs;

[0017] Based on the minimum search radius, determine the position x i '(t) of the UAV within the minimum search area, and form a set B(t) = {x′1(t), x′2(t),..., x' n (t)}, where n is the number of UAVs within the minimum search area;

[0018] Determine the Delaunay triangle connection set L i (t) = {L1(t), L2(t),..., L i (t)} according to the set B(t), and each cooperation set in the triangle connection set consists of three UAVs;

[0019] Determine the cooperation UAV set of the typical user according to the average received power of each cooperation set.

[0020] One of the preferred solutions is that the average received power is:

[0021]

[0022] where \(P\) is the average received power from the \(i\)-th UAV to the typical user, \(\alpha\) is the path loss exponent with \(\alpha\gt2\), and \(\vert\vert x' i (t)\vert\vert\) is the Euclidean distance from the \(i\)-th UAV to the typical user.

[0023] One of the preferred solutions is that the collaborative UAV set is:

[0024]

[0025] where \(U_0(t)\) is the collaborative UAV set and \(I\) is the cardinality of the triangular connection set.

[0026] A coordinated multi-point transmission system based on Poisson-Delaunay triangulation includes a processor, a memory, and an application program for coordinated multi-point transmission based on Poisson-Delaunay triangulation stored on the memory and executable on the processor. When the application program for coordinated multi-point transmission based on Poisson-Delaunay triangulation is executed, the steps of the coordinated multi-point transmission method based on Poisson-Delaunay triangulation are implemented.

[0027] In the above technical solution of the present invention, the coordinated multi-point transmission method based on Poisson-Delaunay triangulation includes the following steps: constructing a spatial distribution model of UAV base stations and dividing the UAV set through Delaunay triangulation; calculating the minimum search radius within the UAV search area and determining the minimum search subset of UAVs according to the UAV set; constructing a collaborative set based on the minimum search subset and determining the collaborative UAV set of the typical user according to the average received power of each collaborative set. The present invention solves the technical problems of high computational complexity and large resource occupation of the existing transmission methods.

[0028] In the present invention, an air-to-ground network uses UAVs as base stations to provide services for ground user equipment. The cooperative transmission among multiple UAVs can significantly improve the network coverage and throughput. Due to the mobility of UAVs, the state of the network link is constantly changing. Therefore, the ground user equipment must regularly reposition or search for its collaborative set. When the number of UAVs increases, the search overhead will continuously increase. The present invention divides the entire UAV set into subsets of the same size by using the divide-and-conquer method, and forms the minimum search subset with the minimum number of UAVs, so as to determine the collaborative UAV set of the typical user in a limited number of minimum search subsets, thereby achieving the effect of minimizing the search overhead. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on the structures shown in these drawings.

[0030] Figure 1 It is a schematic diagram of the coordinated multi-point transmission method based on Poisson-Delaunay triangulation in an embodiment of the present invention;

[0031] Figure 2 It is a schematic diagram of the cooperation set of typical users at a certain moment in an embodiment of the present invention.

[0032] The realization of the purpose of the present invention, functional features and advantages will be further described in conjunction with the embodiments with reference to the drawings. Specific embodiments

[0033] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, rather than all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present invention.

[0034] Moreover, the technical solutions between the various embodiments of the present invention can be combined with each other, but it must be based on the fact that those of ordinary skill in the art can implement them. When the combination of technical solutions conflicts with each other or cannot be implemented, it should be considered that such a combination of technical solutions does not exist and is not within the scope of protection required by the present invention.

[0035] See Figure 1 , according to one aspect of the present invention, the present invention provides a coordinated multi-point transmission method based on Poisson-Delaunay triangulation, wherein the coordinated multi-point transmission method based on Poisson-Delaunay triangulation includes the following steps:

[0036] S1. Construct a spatial distribution model of UAV base stations and divide the UAV set through Delaunay triangulation;

[0037] S2. Calculate the minimum search radius within the search area of the UAVs and determine the minimum search subset of the UAVs according to the UAV set;

[0038] S3. Construct a cooperation set based on the minimum search subset and determine the cooperation UAV set of typical users according to the average received power of each cooperation set.

[0039] Specifically, in this embodiment, the step S1 of constructing the spatial distribution model of the UAV base stations is specifically as follows: All UAVs are distributed as a homogeneous Poisson point process with a density of λ0, equipped with M antennas, and hovering at the same height h; A typical user independent of the UAV distribution is located at the ground origin, i.e., O(0, 0, 0), equipped with a single antenna, and is served by N UAVs in the cooperation set; To improve the service quality of the ground user equipment, coordinated multi-point transmission is adopted. The typical user is served by three UAVs in the cooperation set. The present invention does not make specific limitations and can be specifically set according to needs. The projection of the ground origin on the plane formed by the UAVs is denoted as O'.

[0040] Specifically, in this embodiment, the step S1 of dividing the UAV set by Delaunay triangulation is specifically as follows: According to the spatial distribution model of the UAV base stations, the Delaunay triangulation is constructed by the divide-and-conquer method, and based on each UAV vertex, the target area is triangulated by the Delaunay triangulation method to form the UAV set.

[0041] Specifically, in this embodiment, the step S2 is specifically as follows: The probability that a circle with a radius of R s contains at least one cooperation set is evaluated through the geometric relationship between the UAV density λ0 and the degrees of freedom. Each UAV has six degrees of freedom. Therefore, considering that each cooperation set consists of three UAVs, on average, at least n = 18 UAVs are required to establish a complete cooperation set. Therefore, given the UAV density λ0, the search area of the UAVs should satisfy the inequality Therefore, the minimum search radius is as follows:[[]]

[0042]

[0043] where R smin is the minimum search radius and λ0 is the UAV density;

[0044] The minimum search area is obtained with the minimum search radius, thereby obtaining the minimum search subset within the minimum search area.

[0045] Specifically, in this embodiment, the step S3 is specifically as follows:

[0046] Obtain the distance d k (t) between the UAV located at x k (t) at time t and the typical user, where 1 ≤ k ≤ m and m is the total number of UAVs;

[0047] Based on the minimum search radius, determine the position x i '(t) of the UAV within the minimum search area, and form the set B(t) = {x′1(t), x'2(t),..., x' n(t)}, where n is the number of UAVs in the minimum search area; specifically:

[0048] When d k (t) ≤ R smin , then the UAVs within the minimum search area are screened to form the set B(t) = {x′1(t), x'2(t),..., x' n (t)};

[0049] Determine the Delaunay triangle connection set L i (t) = {L1(t), L2(t),..., L i (t)}, 1 ≤ i ≤ I, where I is the cardinality of the triangle connection set, and each cooperation set in the triangle connection set consists of three UAVs;

[0050] Determine the cooperative UAV set of the typical user according to the average received power of each cooperation set; the cooperative UAV set consists of three UAVs in the cooperation set with the highest average received power serving the typical user, where the fading coefficient takes the average value.

[0051] Specifically, in this embodiment, the average received power is:

[0052]

[0053] where P is the average received power from the i-th UAV to the typical user, α is the path loss exponent, α > 2, and ||x′ i (t)|| is the Euclidean distance from the i-th UAV to the typical user.

[0054] Specifically, in this embodiment, the cooperative UAV set is:

[0055]

[0056] where U0(t) is the cooperative UAV set and I is the cardinality of the triangle connection set.

[0057] Specifically, in this embodiment, referring to Figure 2 , in Python, the Monte Carlo method is used to perform simulation analysis to obtain the cooperation set of the typical user at a certain moment. The basic idea of the Monte Carlo analysis method is to simulate the possible situations of the problem by generating a large number of random numbers, and then estimate the solution of the problem based on the statistical characteristics of these random numbers; through it, the superiority of the coordinated multi-point transmission method based on Poisson-Delaunay triangulation proposed by the present invention in minimizing the overhead for the user to search for its COMP set can be found; where Coop Drones represents the cooperative UAVs, All Drones represents all UAVs, and UE represents the ground user equipment.

[0058] A coordinated multi-point transmission system based on Poisson-Delaunay triangulation, comprising a processor, a memory, and an application program for coordinated multi-point transmission based on Poisson-Delaunay triangulation stored on the memory and executable on the processor. When the application program for coordinated multi-point transmission based on Poisson-Delaunay triangulation is executed, the steps of the coordinated multi-point transmission method based on Poisson-Delaunay triangulation are implemented.

[0059] The above are only the preferred embodiments of the present invention, and do not limit the patent scope of the present invention. Any equivalent structural transformation made by using the content of the specification and drawings of the present invention under the inventive concept of the present invention, or any direct / indirect application in other related technical fields is included in the patent protection scope of the present invention.

Claims

1. A coordinated multi-point transmission method based on Poisson-Delaunay triangulation, characterized in that It includes the following steps: S1. Construct a spatial distribution model of the UAV base stations, and divide the UAV set through Delaunay triangulation; S2. Calculate the minimum search radius within the search area of the UAVs, and determine the minimum search subset of the UAVs according to the UAV set; the minimum search radius is: where R smin is the minimum search radius, and λ0 is the UAV density; S3. Construct a cooperation set based on the minimum search subset, and determine the cooperation UAV set of the typical user according to the average received power of each cooperation set; specifically: Obtain the distance d k (t) between the drone at x at time t and a typical user k (t), 1 ≤ k ≤ m, where m is the total number of drones; Determine the position x of the UAV in the minimum search area based on the minimum search radius i '(t), to form a set B(t) = {x’1(t), x'2(t),..., x' n (t)}, where n is the number of UAVs in the minimum search area; Determine the Delaunay triangle connection set L according to the set B(t) i (t) = {L1(t), L2(t),..., L i (t)}, and each cooperation set in the triangle connection set consists of three drones; Determine the cooperation UAV set of the typical user according to the average received power of each cooperation set; the cooperation UAV set is: where U0(t) is the cooperation UAV set, I is the cardinality of the triangular connection set, and α is the path loss exponent.

2. The collaborative multi-point transmission method based on Poisson-Delaunay triangulation according to claim 1, wherein In step S1, constructing the spatial distribution model of the UAV base stations specifically includes: All UAVs are distributed as a homogeneous Poisson point process with a density of λ0, are equipped with M antennas, and hover at the same height h; a typical user independent of the UAV distribution is located at the ground origin, i.e., O(0, 0, 0), is equipped with a single antenna, and is served by N UAVs in the cooperation set.

3. The collaborative multi-point transmission method based on Poisson-Delaunay triangulation according to claim 2, characterized in that Three UAVs in the cooperation set serve the ground typical user.

4. The coordinated multi-point transmission method based on Poisson-Delaunay triangulation according to any one of claims 1-3, characterized in that, In step S1, dividing the UAV set through Delaunay triangulation specifically includes: according to the spatial distribution model of the UAV base stations, using the divide-and-conquer method to construct the Delaunay triangulation, and based on each UAV vertex, using the Delaunay triangulation method to triangulate the target area to form the UAV set.

5. The coordinated multi-point transmission method based on Poisson-Delaunay triangulation according to any one of claims 1-3, characterized in that, The average received power is: Among them, P is the average received power from the i-th UAV to the typical user, α is the path loss exponent, α > 2, and ||x’ i (t)|| is the Euclidean distance from the i-th UAV to the typical user.

6. A coordinated multi-point transmission system based on Poisson-Delaunay triangulation, characterized in that, It includes a processor, a memory, and an application program for coordinated multi-point transmission based on Poisson-Delaunay triangulation stored on the memory and executable on the processor. When the application program for coordinated multi-point transmission based on Poisson-Delaunay triangulation runs, it implements the steps of the method for coordinated multi-point transmission based on Poisson-Delaunay triangulation as described in any one of claims 1-5.

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