KR20170000556A - Uav allocating method for wireless communication in region of interest and network reconstructing method using uav - Google Patents

Abstract

The present invention relates to a method for recovering a network by an using unmanned aerial vehicle, the method comprising the steps of: allowing at least one unmanned aerial vehicle to collect packet reception rates while moving in a region of interest, at which at least one communication node or AP has been disposed, wherein the region of interest is divided by a grid, the unmanned aerial vehicle moves between a plurality of vertices at which any two of rectilinear lines, constituting the grid, intersect, and the unmanned aerial vehicle collects the packet reception rates for the respective vertices; allowing the unmanned aerial vehicle to determine an average packet reception rate for all vertices included in each region having a predetermined size and a shape which can be generated by using the vertices of the grid; allowing the unmanned aerial vehicle to select a target region, at which the unmanned aerial vehicle is to be disposed, among the regions based on the average packet reception rates; allowing the unmanned aerial vehicle to move to the target region; and allowing the unmanned aerial vehicle to function as the communication node or AP within the target region.

Description

BACKGROUND OF THE INVENTION 1. Field of the Invention [0001] The present invention relates to a method for disposing an unmanned aerial vehicle in a region of interest for wireless network communication and a network restoration method using an unmanned aerial vehicle

The technique described below relates to a technique for restoring a network using an unmanned aerial vehicle.

Various techniques for recovering a failure of a node or an AP constituting a wireless network have been studied. There is a technique for performing a communication node or relay function using a movable communication device.

Korean Patent No. 10-1083056

The technique described below is to find a region where communication is not smooth in a wireless network, and to provide a technique of using an unmanned aerial vehicle disposed in the area as a network repeater.

A method for deploying an unmanned aerial vehicle in a region of interest for wireless network communication includes collecting packet reception rates of a communication node or AP while moving at least one unmanned aerial vehicle at a plurality of points in an area of interest, Determining an average packet reception ratio at a point where the unmanned aerial vehicle is included in the area, determining a target area where the unmanned aerial vehicle will be deployed based on the average packet reception ratio of the unmanned aerial vehicle, .

In the network recovery method using the unmanned aerial vehicle, the at least one unmanned aerial vehicle collects the packet reception ratio while moving at least one communication node or the AP where the AP is disposed. The interested area is classified into a lattice shape, Collecting a packet reception rate for each of a plurality of vertices while moving a plurality of vertices of the vertices of the vertexes of the plurality of vertices, Determining an average packet reception ratio, determining a target area where an unmanned aerial vehicle will be deployed in an area based on an average packet reception ratio of the unmanned aerial vehicle, moving the unmanned aerial vehicle to a target area, And performing a function as an AP.

The technique described below can easily identify the point where the communication is not smooth among the areas where the wireless network equipment is installed using the freely movable unmanned aerial vehicle, and can quickly recover the network by arranging the unmanned aerial vehicle with the communication function.

FIG. 1 shows an example of an unmanned aerial vehicle flying in a region of interest and a region of interest.
FIG. 2 is an example of a route in which an unmanned aerial vehicle is flying in an area of interest.
FIG. 3 shows an example of a process in which two unmanned aerial vehicles search for an area of interest.
FIG. 4 shows another example of a process in which two unmanned aerial vehicles search for an area of interest.
Figure 5 is an example of vertex sets in the region of interest.
6 is an example of a flowchart of a method for restoring a network using an unmanned aerial vehicle.

The following description is intended to illustrate and describe specific embodiments in the drawings, since various changes may be made and the embodiments may have various embodiments. However, it should be understood that the following description does not limit the specific embodiments, but includes all changes, equivalents, and alternatives falling within the spirit and scope of the following description.

The terms first, second, A, B, etc., may be used to describe various components, but the components are not limited by the terms, but may be used to distinguish one component from another . For example, without departing from the scope of the following description, the first component may be referred to as a second component, and similarly, the second component may also be referred to as a first component. And / or < / RTI > includes any combination of a plurality of related listed items or any of a plurality of related listed items.

As used herein, the singular " include "should be understood to include a plurality of representations unless the context clearly dictates otherwise, and the terms" comprises & , Parts or combinations thereof, and does not preclude the presence or addition of one or more other features, integers, steps, components, components, or combinations thereof.

Before describing the drawings in detail, it is to be clarified that the division of constituent parts in this specification is merely a division by main functions of each constituent part. That is, two or more constituent parts to be described below may be combined into one constituent part, or one constituent part may be divided into two or more functions according to functions that are more subdivided. In addition, each of the constituent units described below may additionally perform some or all of the functions of other constituent units in addition to the main functions of the constituent units themselves, and that some of the main functions, And may be carried out in a dedicated manner.

Also, in performing a method or an operation method, each of the processes constituting the method may take place differently from the stated order unless clearly specified in the context. That is, each process may occur in the same order as described, may be performed substantially concurrently, or may be performed in the opposite order.

A wireless network is a network that performs wireless communication. Wireless networks can be classified into various categories. In the present market, various technologies are used according to the communication method or standard to be used. For example, various technologies exist such as a mobile communication network using a communication method such as 3G / LTE, a short-range wireless communication according to IEEE 802.11 (Wi-Fi), and a short-range wireless communication according to IEEE 802.15.4 (Zigbee).

In a wireless network, a user terminal accesses a core network through an Access Point (AP). The user terminal transmits and receives data through a base station of a mobile communication network and an AP device for other short-range wireless communication. The service provider places the AP in the service area considering the geographical features. Therefore, if the AP fails, the communication service is not provided in the vicinity of the AP. Furthermore, areas where it is difficult to install APs due to geographical characteristics can be a transliteration area.

In an ad hoc network, a user terminal transmits data through nodes constituting an ad hoc network. If some of the nodes constituting the ad hoc network fail, a smooth communication service can not be provided.

The technique described below is a technique for restoring a wireless network using unmanned aerial vehicles (UAV). Or a radio shadow area in which a signal of a wireless network is not properly transmitted using an unmanned aerial vehicle. Hereinafter, the unmanned aerial vehicle means a vehicle having a propellant that can fly on its own, such as a drone.

The technique described below consists of two steps. First, the unmanned aerial vehicle is flying through a certain area and searching for a point or area where communication is not smooth in the area. Second, the unmanned aerial vehicle is located at a point where communication is not smooth and operates as an AP or a communication node. The unmanned aerial vehicle functions as a communication node constituting an AP or an ad-hoc network according to a communication method. Therefore, the unmanned aerial vehicle must have a communication module for performing the communication function.

A region that checks whether communication is smooth using an unmanned aerial vehicle is called a region of interest (ROI). The area of interest will typically be the outdoor area where the AP or communication node is located. However, if the wireless communication is used inside the building, the area of interest may be indoor.

For convenience of explanation, the description will be made on the basis of an ad hoc network. The user uses the unmanned aerial vehicle to set an area of interest to the entire ad-hoc network or the ad hoc network as an area of interest. The unmanned aerial vehicle knows the location information of the area of interest in advance. The unmanned aerial vehicle can search the area of interest defined by coordinates using a device such as GPS. Alternatively, the unmanned aerial vehicle may use a sensor device (geomagnetism sensor, acceleration sensor, or the like) capable of detecting a position and a distance moving based on a specific point to search for an area of interest defined based on a point at which the flight starts. In addition, the unmanned aerial vehicle can search the area of interest using various positioning techniques.

Interest Area Discovery Process

First, a process of searching for a point or an area where communication is not smooth while the unmanned aerial vehicle is flying the area of interest will be described. For convenience of explanation, it is assumed that the area of interest has a rectangular shape, and the area of interest is divided into rectangular grid units. It is also assumed that there are no obstacles to the flight in the area of interest.

The unmanned aerial vehicle sets itself a route and moves to explore the area of interest. That is, there is no control device separate from the unmanned aerial vehicle. Of course, the control device connected to the network may determine the route of the unmanned aerial vehicle, and collect information collected by the unmanned aerial vehicle. In this case, the control device may be a device such as a server connected to a network, or a communication device that performs direct communication with an unmanned aerial vehicle.

Figure 1 is an example of an unmanned aerial vehicle flying a region of interest (ROI) and a region of interest. Referring to FIG. 1, it can be seen that the region of interest is rectangular and divided into rectangular grid units. The unmanned aerial vehicle moves along a straight line constituting the grid as shown in FIG. 1 shows the arrangement of communication nodes. Among the communication nodes, a node indicated by a black color is a normally operating node, and a node indicated by a white color is a node where a failure occurs. If a specific node fails, communication failure may occur in a specific area or in the entire area. The failed node can not communicate with the neighboring node. In FIG. 1, the broken path is indicated by a dotted solid line.

Figure 1 shows the unmanned aerial vehicles 50A and 50B. In FIG. 1, the path of movement of the unmanned aerial vehicle 50B is indicated by a bold solid line. The unmanned aerial vehicles 50A and 50B search for points where the current communication is not smooth in the area of interest. Thereafter, the unmanned air vehicle 50B is disposed in an area where packets can not be smoothly transmitted due to a failed node. The unmanned air vehicle 50B plays a role of relaying a packet like a communication node of an ad hoc network. A path for receiving a packet from an adjacent node is indicated by an arrowed dotted line. The unmanned aerial vehicle 50B transmits the received packet to another adjacent node according to the route. This is an example of restoring a faulty network using the unmanned air vehicle 50B.

FIG. 2 is an example of a route in which an unmanned aerial vehicle is flying in an area of interest. The area of interest is composed of a square grid and has m x m vertices. For convenience of explanation, N (North), S (South), E (East) and W (West)

The unmanned aerial vehicle collects network information while visiting all the peaks of the area of interest. Various techniques can be used for the method or algorithm for the unmanned aerial vehicle to visit the apex of the area of interest. Whatever algorithm is used, the unmanned aerial vehicle can visit all the peaks of the area of interest.

On the other hand, two or more unmanned aerial vehicles may be used in the process of checking the area of interest. When two or more unmanned aerial vehicles are moving, each unmanned aerial vehicle can exchange information so that the visiting vertices do not overlap. As described above, the unmanned aerial vehicle can perform constant data communication with the communication node of the ad hoc network. Therefore, if the unmanned aerial vehicle recognizes other unmanned aerial vehicles in the middle of the flight, information about the vertices visited or information gathered from the visited vertices can be exchanged. In this case, each unmanned aerial vehicle determines a vertex that has not been searched yet, and searches for an unexplained vertex.

Fig. 2 shows an example in which the unmanned aerial vehicle moves in a zigzag-like copper line in one direction. In FIG. 2, the length of the unmanned aerial vehicle traveling in one direction and passing in the zigzag direction is represented by L. In FIG. 2, a form (L = 2) having two rectangular grids in zigzag units is shown as an example.

The unmanned aerial vehicle can move to eight routes based on the starting point. The eight routes that can be traveled are NE, NW, SE, SW, EN, ES, WN, and WS. The paths that travel in the E direction are NE and SE. Even in the same direction, there are two paths (NE and SE) according to the vertex to be initially selected. The unmanned aerial vehicle can select one of the two routes by selecting the first visit vertex (start vertex). The unmanned aerial vehicle may select a starting vertex in a predetermined direction, or may randomly select a starting vertex.

The unmanned aerial vehicle moves to one of the eight routes based on the starting point. The algorithm for moving the unmanned aerial vehicle will be described. Of course, the algorithm described below is an example in which an unmanned aerial vehicle can search an area of interest. The unmanned aerial vehicle creates a route to visit when moving from the current position (starting point) to one direction before moving. This path is called the expected path. According to FIG. 2 (a), the unmanned aerial vehicle can generate up to eight estimated paths in advance. The number of anticipated routes that can be created at the starting point of the unmanned aerial vehicle begins to vary. The unmanned aerial vehicle can select the route having the longest distance to the boundary of the interested area among the plurality of expected routes.

In FIG. 2, the possible paths for the unmanned aerial vehicle 50C are eight. In FIG. 2, an SE and an N-direction WN of the unmanned air vehicle 50C are shown by bold solid lines. At present, the unmanned aerial vehicle (50C) is the route that travels to the boundary of the area of interest at the longest route in the E direction and the S direction. Currently, the unmanned aerial vehicle (50C) has 6 straight lines up to the E direction boundary and 6 straight lines up to the S direction boundary. Therefore, NE, SE, WS, and ES all have the same length. In this case, the unmanned aerial vehicle 50C can arbitrarily select one of the longest paths and start moving.

When the unmanned aerial vehicle moves to a specific vertex while traveling, it stores and manages the vertex visited. An object that records a vertex visited by an unmanned aerial vehicle is called a visit list. The unmanned aerial vehicle can use the visit list to find out the peak that the user visited in the area of interest. The unmanned aerial vehicle knows the location and identifiers (IDs) of the vertices of interest and adds the identifiers of the vertices to the visited vertex list when the unmanned aerial vehicle visits a specific vertex.

FIG. 3 shows an example of a process in which two unmanned aerial vehicles search for an area of interest. In FIG. 3, a portion indicated by a solid line indicates a path that the first unmanned aerial vehicle 50E has searched for, and a portion indicated by a dotted line indicates a path that the first unmanned aerial vehicle 50E should search for at a current point. In FIG. 3, a circle denoted by a circle means a peak point that the second unmanned aerial vehicle 50F has already visited.

If a plurality of unmanned aerial vehicles search for an area of interest, they exchange information that each person searches at points adjacent to each other. One unmanned aerial vehicle merges the visit list received from other unmanned aerial vehicles with the visit list it holds. In order to do this, all unmanned aerial vehicles must share information about the area of interest, vertex information, etc. in advance.

In FIG. 3, the rows and columns constituting the grid of the area of interest are numbered to indicate the position of the vertices. For example, in FIG. 3 (a), the first unmanned aerial vehicle 50E is located at the v _3,4 position, and the second unmanned air vehicle 50F is located at the v _1,4 position. In FIG. 3, the position of the vertex is shown as an example.

Referring to FIG. 3 (a), the first unmanned aerial vehicle 50E and the second unmanned aerial vehicle 50F are located at an adjacent distance. It is assumed that the first unmanned aerial vehicle 50E and the second unmanned aerial vehicle 50F can communicate with each other at an adjacent distance. The first unmanned air vehicle 50E delivers the first visited list held by the first unmanned air vehicle 50E to the second unmanned air vehicle 50F and the second unmanned air vehicle 50F transmits the second visited list held by the first unmanned air vehicle 50E to the first unmanned air vehicle 50E, . The first unmanned aerial vehicle (50E) and the second unmanned aerial vehicle (50F) merge the visited list received from the relative unmanned aerial vehicle into its own list.

When the first unmanned aerial vehicle (50E) searches for an area of interest along a predicted path, a vertex to be visited next may already be on the visited list. In this case, the vertex to visit next may be the vertex visited by another unmanned aerial vehicle, or it may be the vertex that the user has already visited.

After exchanging the visited list, the first unmanned aerial vehicle 50E must move to the next vertex according to its expected route. But then the first vertex (v _2,4) should visit the unmanned air vehicle (50E) has already visited vertex is the second unmanned aircraft. Algorithms may allow the visit of overlapping vertices, but in principle the unmanned aerial vehicle does not visit the vertices visited by other unmanned aerial vehicles. Therefore, the first unmanned aerial vehicle 50E must go to a new route without visiting the next vertex (v _2,4 ).

Referring to FIG. 3 (a), the first unmanned aerial vehicle 50E finds neighboring vertices that have not visited at the current position (v _3,4 ). Considering the path that the first unmanned aerial vehicle 50E moves diagonally, all the neighboring vertices may be eight. It is assumed that the first unmanned aerial vehicle 50E finds one of the N, S, E, and W neighbors. A vertex that has not yet visited among the four neighbor vertices is the vertex (v _3,5 ) in the E direction.

Referring to FIG. 3 (b), the first unmanned aerial vehicle 50E moves to an unvisited neighboring vertex (v _3,5 ), and then determines a predicted path again at a new position. The first unmanned aerial vehicle 50E estimates a route that can be moved at a new location, and determines a route that is the longest distance from the boundary of the area of interest as a predicted route. The first unmanned aerial vehicle 50E anticipates all the paths in the movable direction at the current position. At this time, it is preferable that the first unmanned aerial vehicle 50E excludes directions in which apexes that have already visited are included, and anticipates paths in other directions. Referring to FIG. 3 (b), neighboring vertices that have already visited at the position (v _3,5 ) of the first unmanned aerial vehicle 50E are v _3,4 and v _2,5 . In FIG. 3 (b), the vertex visited by the first UAV 50E is indicated by a dashed line, and the vertex visited by the second UAV 50F is indicated by a black color. The paths that can be traveled without passing through the vertices already visited by the first unmanned aerial vehicle 50E are SE and ES. The ES path having the longest length from the first unmanned aerial vehicle (50E) movable path to the boundary of the interested area is selected as the expected path. In Fig. 3 (b), the new predicted path is indicated by a dotted line.

FIG. 4 shows another example of a process in which two unmanned aerial vehicles search for an area of interest. It is assumed that the first unmanned aerial vehicle 50E and the second unmanned aerial vehicle 50F exchanged visit lists with each other. In FIG. 4, a solid line indicates a path that the first unmanned aerial vehicle 50E has searched for, and a dotted line indicates a path that the first unmanned aerial vehicle 50E should search for at the current point.

Referring to Figure 4 (a), the first vertex (v _2,4) are unmanned air vehicles (50E) to be moved to the next along the predicted path is already visited vertex. Therefore, the first unmanned aerial vehicle 50E first searches for neighboring vertices that can be moved at the current position. However, at the current position (v _3,4 ) of the first unmanned aerial vehicle 50E, neighboring vertices are all visited vertices.

In this case, the first unmanned aerial vehicle 50E moves directly to the closest vertex that has not been visited among the vertices of the entire area of interest using the visiting list. When the closest vertex is more than two, the first unmanned aerial vehicle 50E selects one of the closest vertices and moves. Referring to FIG. 4B, the first unmanned aerial vehicle 50E has moved to the closest vertex v _5,4 . Now, at the new location, the first unmanned aerial vehicle 50E determines a new expected route. The first unmanned air vehicle 50E selects the route that is the farthest from the movable position at the new position (v _5,4 ) to the boundary of the area of interest. (v _5,4 ), SE, SW, ES and WS are the paths through which the first unmanned aerial vehicle 50E can move. The longest path up to the boundary of the region of interest is the SE. Therefore, the first unmanned aerial vehicle 50E determines the SE path as a predicted path.

Finally, if the unmanned aerial vehicle has no more vertices to move (ie, if all vertices are visited), the search for the area of interest ends.

On the other hand, unmanned aerial vehicles can fly around the area of interest with various patterns. 2 to 4, only the zigzag pattern is shown as an example. However, the unmanned aerial vehicle can move in various patterns of movement paths having certain rules. Furthermore, unmanned aerial vehicles may visit random peaks that have not been visited without certain rules.

The unmanned aerial vehicle moves along the expected route and confirms whether the communication is smooth at the vertices when the new vertex is reached. The unmanned aerial vehicle transmits a certain test packet and receives the feedback packet in response to the test packet from the communication node of the ad hoc network in the vicinity. The test packet and the feedback packet are predetermined, and upon receiving the test packet, the communication node transmits a feedback packet including certain data. At this time, a plurality of communication nodes may exist around the unmanned aerial vehicle. In this case, a plurality of communication nodes transmit feedback packets.

The unmanned aerial vehicle records the packet reception rate (PRR) of the feedback packet received at the visited vertex. The unmanned aerial vehicle stores the identifier of the currently visited peak, the identifier of the communication node that transmitted the feedback packet, and the reception rate of the feedback packet transmitted by the corresponding communication node. The unmanned aerial vehicle performs the same process for all vertices included in the area of interest while moving. A table in which a PRR is recorded while visiting a vertex is called a reception ratio table. The reception ratio table stores the reception rate at which each of the vertices, the communication node that transmitted the feedback packet at the vertex, and the feedback packet transmitted from each communication node. The unmanned aerial vehicle may transmit the test packet at the same vertex several times and store the average reception rate of the feedback packet arriving in response to the test packet in the reception rate table.

Meanwhile, when a plurality of unmanned aerial vehicles create their own reception ratio tables while moving around the area of interest, when the plurality of unmanned aerial vehicles meet at the adjacent vertices, the reception ratio tables created by the plurality of unmanned aerial vehicles can be exchanged. Ultimately, if you use multiple unmanned aerial vehicles, you will be able to search the area of interest more quickly.

The following is the numeric code for the algorithm that the unmanned aerial vehicle moves through the area of interest.

The following is an algorithm for the process of creating the reception table while the unmanned aerial vehicle moves around the area of interest.

Arrangement of unmanned aerial vehicles

The unmanned aerial vehicle searches all the vertices of the area of interest, and after completing the reception table, determines the area or point where communication is not smooth in the current area of interest. The unmanned aerial vehicle places itself or other unmanned aerial vehicles functioning as a communication node at a specific point, and then functions as a communication node of the ad hoc network. It uses a unmanned aerial vehicle to find a network hole that hinders the routing function of the network, and also uses the unmanned aerial vehicle to drill the network hole. The network hole means a point or an area where communication is not smooth. The network hole may be caused by a failure of a specific communication node, or may occur due to a wrong placement of the initial communication node. Further, in the case of a mobile communication network or the like, the unmanned aerial vehicle can function as an AP. Hereinafter, the process of disposing the unmanned aerial vehicle will be described.

A separate control device connected to the unmanned aerial vehicle and the network may control the placement of the unmanned aerial vehicle, but the unmanned aerial vehicle may determine the position where the unmanned aerial vehicle is to be placed based on the information given to it.

When the unmanned aerial vehicle searches for all the areas of interest, a reception ratio table is prepared for all the vertices included in the area of interest. The reception ratio table includes the packet reception ratio (PRR) received from the ID (k) of the communication node in the ID (j) of the vertex. If the number of communication nodes arranged in the area of interest is N and the number of vertices is M (= m ² ), the collected packet reception rate can be expressed as [PRR] j, k. Where 1? K? N and 1? J? M.

There will be a limited number of unmanned aerial vehicles that function as communication nodes. Also, since the operation of the unmanned aerial vehicle itself is a kind of cost, it is desirable to arrange the unmanned aerial vehicle as efficiently as possible. The position of the unmanned aerial vehicle is determined regardless of the position of the communication node. For example, the unmanned aerial vehicle is not disposed at the position of the communication node where the current failure occurs. Hereinafter, the criteria for deploying unmanned aerial vehicles should be explained.

Instead of using one vertex as the basis for deploying the unmanned aerial vehicle, we use a set of vertices that contain multiple vertices. Of course, it would be possible to deploy an unmanned aerial vehicle at the peak of the average packet reception rate based on one vertex. The reason for using the vertex set is that the coverage of the deployed unmanned aerial vehicle does not overlap with each other.

Figure 5 is an example of vertex sets in the region of interest. FIG. 5 shows a region of interest having nine rectangles each having a width and a length. It is assumed that the vertex set has a square shape with a size of n × n. In FIG. 5, a vertex set having a size of 4 × 4 is shown. In Fig. 5, there are 64 vertex sets that can be generated. S ₁ and S ₂ have a common vertex {v _0,1 , v _0,2 , v _0,3 , v _1,1 , v _1,2 , v _1,3 , v _2,1 , v _2,2 , v ₀ , ₃ , v _3,1 , v _3,2 , v _3,3 }, S ₁ and S ₉ have a common vertex {v _1,0 , v _1,1 , v _1,2 , v _1,3 , v _2,0 , v _2,1 , v _2,2 , v _2,3 , v _3,0 , v _3,1 , v _3,2 , v _3,3 }. In FIG. 5, S ₁ , S ₂ , S ₈ , S ₉ , S ₅₇ and S ₆₄ among the vertex sets that can be generated in the region of interest are illustratively shown.

A set of vertices constituted by a plurality of vertices forms an area having a constant shape. FIG. 5 shows a vertex set of a square shape. However, vertex sets of other shapes may be possible. The size of the area formed by the vertex set is related to the communication coverage of the unmanned aerial vehicle. According to the number of available unmanned aerial vehicles and the communication coverage of unmanned aerial vehicles, the arrangement algorithm of unmanned aerial vehicles can be changed. In order to use the unmanned aerial vehicle efficiently, the coverage of the unmanned aerial vehicle disposed in the interested area can be prevented from being overlapped with each other. In this case, it is desirable that the size of the area constituted by the vertex set is equal to or slightly larger than the communication coverage of one unmanned aerial vehicle. As a result, the number of vertices constituting the vertex set can be changed according to the communication coverage of the unmanned aerial vehicle.

The basic conditions for deploying the unmanned aerial vehicle are (i) arranging the coverage of unmanned aerial vehicles so that they do not overlap each other, and (ii) preferentially finding the vertex set with the weakest average PRR among the vertex sets. At this time, we exclude the vertex set whose PRR is 0 (zero). A set of vertices with a PRR of 0 means that the packet reception rate is 0 at all vertices belonging to the set of vertices. Since the size of the area constituting the vertex set is larger than the coverage of the unmanned aerial vehicle, even if the unmanned aerial vehicle is placed at the position of the vertex set of PRR 0, it is impossible to overcome all of the communication obstacles.

으로 표현된다.

는

에 속한 정점이고,

은

에 속한 정점의 개수이다. 관심 지역은 정점 집합으로 구분되기 때문에 모든 정점 집합에 속한 정점은 관심 지역 전체의 정점에 해당한다. 즉,

이다. The vertex set is

.

The

Is a vertex belonging to < RTI ID =

silver

Is the number of vertices belonging to. Since the region of interest is divided into a set of vertices, the vertices belonging to all vertex sets correspond to the vertices of the entire region of interest. In other words,

to be.

In simple terms, the area where the unmanned aerial vehicle is deployed is the set of vertexes with the smallest average packet reception rate among vertex sets. The average packet reception rate of the vertex set is an average value of the packet reception rate measured at the vertices belonging to the vertex set. An unmanned aerial vehicle can be placed at the midpoint of a selected set of vertices. If a plurality of unmanned aerial vehicles are arranged, an unmanned aerial vehicle can be arranged by selecting a vertex set in descending order of the average packet reception rate of vertex sets.

Furthermore, a plurality of vertex sets in which an unmanned aerial vehicle is disposed can select a set that does not have apexes in common with each other. In other words, if S _i and S _j are chosen as the area in which the unmanned aerial vehicle will be deployed, S _i ∩ S _j = Ø. In Fig. 5, S ₁ and S ₂ can not be selected at the same time, even if S ₁ and S ₂ are two vertex sets with the smallest average packet reception ratio. This is for more efficient deployment of unmanned aerial vehicles with limited numbers.

Hereinafter, an algorithm for determining the placement of unmanned aerial vehicles will be described using a binary integer problem. First, the variables and indicator functions used in the following equations are described. P is the number of unmanned aerial vehicles that can be placed in the area of interest. The indicator function J _i indicates that the vertex set S _i should be selected as the area where the unmanned aerial vehicle is to be placed. The indicator function I _{i, j} indicates that the vertex v _i belonging to the vertex set S _i and the vertex v _j belonging to the area where the unmanned aerial vehicle is to be placed should be selected.

The vertex set in which the unmanned aerial vehicle is to be placed is selected among various vertex sets that can be composed of the vertices included in the interested area by using the following equation. Basically, among vertex sets that can be generated in the area of interest, a vertex set satisfying the following equation (1) is selected.

은 정점 v_j에서 주변에 있는 통신 노드의 평균 패킷 수신율을 의미한다. 수학식 1은 결국 정점 집합 중에 평균 패킷 수신율이 가장 낮은 정점 집합을 선택한다는 의미이다. 정점 중에 패킷 수신율이 0인 곳을 포함하는 정점 집합은 가능하면 배제하는 것이 바람직하다. 따라서

가 0인 정점은 0이 아닌 1의 값을 갖도록 한다.In Equation (1)

Denotes the average packet reception rate of neighboring communication nodes at the vertex v _j . Equation (1) means that a vertex set having the lowest average packet reception rate among vertex sets is selected. It is preferable to exclude the vertex set including the place where the packet reception ratio is 0 among the vertices as much as possible. therefore

The value of a vertex of 0 is a value of 1 rather than 0.

Furthermore, the vertex set can be selected by adding the following equations (2) to (4) to the equation (1).

Equation (2) does not include a common vertex in a selected vertex set when selecting a vertex set.

In Equation (3), when one vertex set S _i is selected, all the vertices v _j belonging to S _i are selected.

Equation (4) limits the set of vertices selected to correspond to the maximum number of unmanned aerial vehicles.

As described above, the unmanned aerial vehicle can function as a communication node of an ad hoc network. It may also serve as a repeater or AP for other wireless networks than an ad hoc network. For example, the unmanned aerial vehicle collects the packet reception rate in the area of interest while flying the area of interest in which the base station (or the AP) of the mobile communication network is disposed, finds an area or point where communication is not smooth in the area of interest, have. The unmanned aerial vehicle can then perform the AP role.

6 is an example of a flowchart of a method 200 for restoring a network using an unmanned aerial vehicle.

At least one unmanned aerial vehicle collects a packet reception ratio (210) while moving through a region of interest where one communication node or AP is located. At this time, the interested area can be classified into a grid shape as shown in FIG. 2 and the like, and the unmanned aerial vehicle collects the packet reception ratio while moving a plurality of vertices where the straight lines forming the grid meet each other.

The unmanned aerial vehicle confirms whether the visit to the plurality of vertices of the interested area is completed (220). If the visit to all the points is not completed, the unmanned aerial vehicle moves to a vertex that has not yet visited (230).

When the unmanned aerial vehicle visits all the vertices included in the area of interest and collects the packet reception ratio for each point, as shown in FIG. 5, the unmanned aerial vehicle calculates the average packet reception ratio (240).

The set includes a plurality of vertices that identify the region of interest. The set corresponds to an area having a constant size and shape. The shape of the region may be square as shown in Fig. The unmanned aerial vehicle calculates a value obtained by averaging the packet reception rates of a plurality of vertices contained in each set for all sets that can be generated using a plurality of vertices in an area of interest.

The unmanned aerial vehicle determines a target set in which a plurality of sets of unmanned aerial vehicles will be deployed based on the average packet reception ratio for the set (250). The unmanned aerial vehicle determines the target set as the set having the lowest average packet reception rate among all possible sets for the area of interest. When there are a plurality of unmanned aerial vehicles that operate as a communication node or an AP, the unmanned aerial vehicle has a common target vertex among all the settable units for the interested area, and a target set of the number of unmanned aerial vehicles .

The unmanned aerial vehicle then moves to an area (target area) corresponding to the determined target set (260), and the unmanned aerial vehicle functions as a communication node or an AP in the target area (270) Performs communication with the peripheral node at the corresponding position, or performs communication with the user terminal.

It should be noted that the present embodiment and the drawings attached hereto are only a part of the technical idea included in the above-described technology, and those skilled in the art will readily understand the technical ideas included in the above- It is to be understood that both variations and specific embodiments which can be deduced are included in the scope of the above-mentioned technical scope.

50A, 50B, 50C, 50D, 50E, 50F: unmanned vehicle

Claims (12)

Collecting a packet reception ratio of a communication node or an AP while moving at least one unmanned aerial vehicle at a plurality of points in a region of interest;
Determining an average packet reception rate at a point where the unmanned aerial vehicle is included in the area in a unit area having a predetermined size and shape in the area of interest;
Determining a target area of the unmanned aerial vehicle to which the unmanned aerial vehicle is to be placed based on the average packet reception rate; And
And moving the unmanned aerial vehicle to the target area, wherein the unmanned aerial vehicle is a communication node or an AP. The method according to claim 1,
In the collecting step
Wherein the ROI is divided into a grid shape and the ROI includes a plurality of vertices in which straight lines making up the grid meet with each other while the ROV is moving along the plurality of vertices, A method for deploying an unmanned aerial vehicle in a region of interest for wireless network communication. The method according to claim 1,
In the collecting step
When two or more unmanned aerial vehicles collect the packet reception rate, if the unmanned aerial vehicles are located at points where the mutual non-flying objects can communicate with each other, How to place a flight. The method according to claim 1,
In the collecting step
Wherein the unmanned aerial vehicle does not move to the point where the unmanned air vehicle has already visited or the point where the unmanned air vehicle has already visited when moving the plurality of points, How to place an unmanned aerial vehicle in your area of interest. The method according to claim 1,
The collecting step
Wherein the unmanned aerial vehicle transmits test packets at least once at one of the plurality of points; And
Storing the packet reception rate at the one point according to whether the unmanned aerial vehicle is receiving a feedback packet transmitted by the communication node or the AP in response to the test packet; How to deploy unmanned aerial vehicles in the area. The method according to claim 1,
In the determining step
Wherein the unmanned aerial vehicle determines an area having the lowest average packet reception rate among all the area units that can be set for the area of interest as the target area. The method according to claim 1,
In the determining step
When there are a plurality of said unmanned aerial vehicles operating as communication nodes or APs,
Wherein the unmanned aerial vehicle has a common interest point for wireless network communication that determines the target area by the number of the unmanned aerial vehicles according to the order of lowest average packet reception rate, How to deploy unmanned aerial vehicles in the area. Wherein at least one unmanned aerial vehicle collects packet reception ratios while moving at least one communication node or an area of interest in which an AP is disposed, wherein the area of interest is classified into a grid shape, and the unmanned air vehicle has a plurality of Collecting a packet reception ratio for each of the plurality of vertices while moving a vertex;
Determining an average packet reception rate of all the vertices included in the area for all the areas in the area unit having the constant size and shape that the unmanned aerial vehicle can generate at the plurality of vertexes;
Determining a target area of the unmanned aerial vehicle to which the unmanned aerial vehicle is to be placed based on the average packet reception rate;
Moving the unmanned air vehicle to the target area; And
Wherein the unmanned aerial vehicle performs a function as a communication node or an AP in the target area. 9. The method of claim 8,
In the collecting step
A method for recovering a network using an unmanned air vehicle in which two or more unmanned aerial vehicles collect the packet reception rate and exchange packet reception rates collected at visited points and visited points when different unmanned aerial vehicles are located at communication points with each other. 9. The method of claim 8,
In the determining step
Wherein the unmanned aerial vehicle determines an area having the lowest average packet reception rate as the target area among all the area units configurable for the area of interest. 9. The method of claim 8,
In the determining step
When there are a plurality of said unmanned aerial vehicles operating as communication nodes or APs,
The unmanned aerial vehicle system according to claim 1, wherein the unmanned aerial vehicle has a common point among all area units that can be set for the area of interest, and determines the target area by the number of the unmanned aerial vehicles Way. 9. The method of claim 8,
In the moving step
Wherein the unmanned aerial vehicle moves to a center point of the target area.

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