CN113242566B - A UAV base station selection method under occlusion effect - Google Patents

Abstract

The invention researches and discusses the shielding problem of buildings in dense urban areas, and provides a method for selecting unmanned aerial vehicle base stations under a shielding effect. The user selects the nearest unmanned aerial vehicle base station which is not shielded by the building in the connectable range as the service unmanned aerial vehicle base station, and when the unmanned aerial vehicle base station which is not shielded by the building does not exist, the nearest unmanned aerial vehicle base station which is shielded by the building once is selected as the service base station. When the coverage area of a single unmanned aerial vehicle base station is small, namely the angle of an unmanned aerial vehicle antenna is small, the coverage rate of the unmanned aerial vehicle base station covered by a building to the service of the user is effectively improved based on the provided unmanned aerial vehicle base station selection method considering the shielding effect.

Description

A UAV base station selection method under occlusion effect

technical field

The present invention relates to the technical field of wireless communication, and in particular to communication between UAV base stations in the fifth generation of mobile communication (Beyond 5thGeneration, B5G) and the sixth generation of mobile communication (6th Generation, 6G) in the future.

Background technique

In the face of the explosive growth of mobile data traffic in the future, UAV communication, as one of the main research directions for B5G to expand the communication space, has attracted extensive attention from academia and industry. Ground sites often have long deployment cycles and high costs, making existing ground site deployment solutions unsuitable for highly dynamic business scenarios (such as heating supplementary scenarios with large capacity requirements and blind patching scenarios with high coverage requirements, etc.), and cannot be realized The goal of accessing sites on-demand by the spatio-temporal distribution of terrestrial mobile users. Due to the characteristics of low cost, rapid deployment, and wide coverage, drones can be used as air base stations to provide communication services for ground users. Disaster areas meet the needs of rapid communication recovery, as an effective supplement to ground base station communication is the main research direction of future mobile communication.

In the future mobile communication system, UAV as a base station for wireless communication services is a technology that can meet high complexity and dynamic data requirements. Compared with the existing ground cells and satellite communications, UAV base station communication has the following advantages: better mobility makes it possible to quickly deploy stations on demand, since the links with ground users and macro stations are mostly line-of-sight ( The line-of-sight (LOS) path increases the capacity of data transmission. UAV base station communication is mostly used in blind and heat supplementary scenarios, that is, to provide services for areas where ground base stations are not deployed and traditional communication is interrupted, or to provide good link performance and capacity improvement in user-intensive areas. In addition, UAV base stations can effectively improve link quality and user capacity by using beams to serve users.

Since UAV base stations are often used in heating scenarios and ground mobile users are densely distributed in urban areas, based on the actual wide beam model, the beam pitch angle and deployment height of UAV base stations will directly affect the beam coverage of UAV base stations. In addition, the shading effect of buildings and the penetration loss caused by them need to be considered when analyzing the change of UAV channel conditions in an urban environment.

Contents of the invention

The present invention studies and discusses the occlusion problem of buildings in dense urban areas, and proposes a method for selecting UAV base stations under the occlusion effect. This method considers that the beam still has a certain energy after penetrating a building, that is, the penetration loss factor If it is not zero, the user selects the nearest unobstructed drone base station within the connectable range as the serving drone base station. When there is no unobstructed drone base station, the user selects the nearest unobstructed drone base station The UAV base station that is blocked by objects once is used as the serving base station.

The UAV base station selection method considering occlusion effect of the present invention comprises the following steps:

Step 200, determine the base station range of the drone that the user can connect to according to the deployment parameters of the drone and the antenna configuration.

的关系表达式如下The wide-beam UAV base station is deployed at a height h from the ground in dense urban areas, and the antenna angle is set to θ, θ∈(0, π/2). Considering the influence of the antenna angle of the UAV on the beam gain, the UAV base station Beam gain G and beam azimuth

The relational expression is as follows

Among them, the side lobe gain of the beam is approximately 0, so the UAV base station can only provide services to users within the coverage of the beam, and the signal strength outside the coverage of the beam is almost zero. Therefore, the range of wide-beam UAV base stations that users can connect to is a circular area with the user as the center and a radius of htanθ.

Step 210, according to the acquired environmental parameters of the dense urban area, through three-dimensional space occlusion modeling, determine the occlusion of the link between any user and the UAV base station within the connectable range, and introduce the penetration loss factor to obtain the penetration of the link loss.

According to the distribution of the number of blocked buildings, the penetration loss S of the link between the user and the UAV base station is determined, and its calculation formula is:

S = γ ^K' ,

Among them, γ is the power loss ratio after the signal passes through the buildings in a certain area, that is, the penetration loss factor. Both the user's useful signal and the interference signal need to consider the impact of building blockage. For large buildings with multiple walls and mmWave beam scenarios with more severe penetration loss through buildings, γ = 0 assuming all buildings are impenetrable. The present invention studies the beam model of the wide beam. In the urban environment, buildings will block the beam of the UAV base station, and the penetration loss of the building is small, but it will still affect the user, that is, γ>0.

Both the user's useful signal and the interference signal need to consider the blocking effect of the building.

In the above formula, K' is the number of blocked buildings on the connection between the UAV base station and the user's three-dimensional space, K' obeys the Poisson distribution, and the expression is:

Among them, R is the distance from the user to the horizontal projection of the UAV base station; p=λE[L]E[W] is the normalized urban density obtained from the building density λ, and E[L] and E[W] are respectively The average length and width of the building, p=0 when there is no building on the ground, p=1 when the building completely covers the ground; β is related to the average length and width of the building and the building density, expressed as:

η is the blocking probability of buildings in three-dimensional space, and the calculation formula is:

为用户和无人机基站水平投影连线上对应位置处的建筑恰好阻塞用户与该无人机基站信道的高度。对建筑物的高度分布函数f_H(h′_b)从地面到

高度处进行积分，即得到在二维空间建筑物阻塞用户和无人机基站水平投影连线但三维空间无法阻塞用户与该无人机基站信道的概率，进而得到三维空间的建筑物阻塞概率η。Among them, the upper limit of points

It is the height at which the building at the corresponding position on the horizontal projection line between the user and the UAV base station just blocks the channel between the user and the UAV base station. For the building height distribution function f _H (h′ _b ) from the ground to

Integrate at the height, that is, the probability that the building blocks the horizontal projection connection between the user and the UAV base station in the two-dimensional space but cannot block the channel between the user and the UAV base station in the three-dimensional space, and then obtains the building blocking probability η in the three-dimensional space .

Among them, the expression of the height distribution function f _H (h′ _b ) of the building is as follows, considering that it obeys the Rayleigh distribution with the average height of the building as the characteristic value,

h_b为一定范围内建筑物的平均高度。in,

h _b is the average height of buildings within a certain range.

P _{K'=0} =e ^-η(βx+p/4) corresponds to the signal not experiencing penetration loss. When the penetration loss factor is large, it is considered that the probability of K' being greater than 1 is small, and the huge penetration loss of the signal passing through buildings twice or more has negligible impact on users.

Step 220, according to the occlusion of the link between the user and the UAV base station within the connectable range determined above and the penetration loss of the link, select the UAV base station and determine the user service base station. The rules of UAV base station selection method considering occlusion effect are as follows:

When there is a UAV base station on the LOS path within the user's connectable range htanθ, the user is served by the beam of the UAV base station on the LOS path, that is, there is no penetration loss of the useful signal. The user selects the drone base station with the largest RSRP as its serving base station. At this time, the user is served by the nearest LOS drone base station, and the rest of the drone base stations within the connectable range are interference base stations. The interference base stations may include LOS paths and NLOS paths. UAV base station or UAV base station with NLOS path.

In this case, within the Htanθ distance, the beam of the UAV is not blocked by the building, that is, the LOS path from the serving UAV to the user, and the horizontal projection x of the line connecting the user to the base station of the serving UAV In , the path from other UAV base stations to the user is blocked by buildings, so the expression of the probability density function is:

Among them, μ is the deployment density of UAV base stations, and the expression of U(x) is:

When there is no UAV base station with LOS path within the user’s connectable range htanθ, the user is served by the beam of UAV base station with non-line-of-sight (NLOS) path, that is, there is penetration of useful signals loss. If the signal passes through buildings twice or more, the impact on the user is negligible. At this time, the user chooses the nearest UAV base station that is once blocked by the building as the serving base station, and can connect to other UAV base stations within the range. It is an interference base station, and the interference base stations are all UAV base stations on the NLOS path.

In this case, the paths from the beams of all UAVs to the user within the Htanθ distance are blocked by buildings, and the UAV with the closest distance is selected as the service UAV for the user, that is, the service UAV to the user is the NLOS path, then the probability density function is

Beneficial effect

The present invention proposes a UAV base station selection method under the occlusion effect, aiming at the situation that the UAV base station signal received by the user may have penetration loss caused by the occlusion of the user-UAV base station link by buildings in dense urban areas. Based on the existing wide beam model, the antenna angle and deployment height of the drone base station will affect the coverage of a single drone base station. In urban environments, buildings will block the beam of the drone base station, and the wide beam is used in The building penetration loss of the UAV base station is small, but it will still affect the user. Therefore, when there is no UAV base station with a LOS path within the user's connectable range, the user chooses the nearest building to block it once. UAV base station service.

Considering the occlusion effect of UAV base station selection, there are two cases of LOS path UAV and UAV base station blocked by buildings as user service UAV base station. The beam coverage performance of the user-centered UAV base station network in the urban environment is analyzed. When the coverage of a single UAV base station is small, that is, when the UAV antenna angle is small, the UAV base station blocked by buildings is considered. Service to users will effectively increase coverage.

Description of drawings

Fig. 1 is the UAV base station network scene diagram considering occlusion effect of the present invention;

Fig. 2 is the algorithm implementation flowchart of the present invention;

Fig. 3 is under the unmanned aerial vehicle base station selection that considers occlusion effect of the present invention, the signal-to-interference ratio (Signal-to-Interference Ratio, SIR) coverage ratio changes relation figure with unmanned aerial vehicle antenna angle;

Fig. 4 is a relationship diagram of the variation of SIR coverage with the ratio of UAV/average building height under different penetration loss conditions of the present invention.

Detailed ways

Embodiments of the present invention will be described in detail below in conjunction with the accompanying drawings.

The present invention proposes a method for selecting a UAV base station under the occlusion effect for scenes where buildings are occluded in dense urban areas. The network model diagram is shown in Figure 1. Considering the actual coverage model of the wide beam, that is, the influence of the antenna angle of the UAV on the beam gain, the UAV base station can only provide services to users within the coverage area of the beam, and the signal strength outside the coverage area of the beam is almost zero. Therefore, the coverage of a single UAV will be affected by the deployment height and antenna angle of the UAV base station. Correspondingly, the range that users can connect to the UAV base station is limited by the deployment height and antenna angle of the UAV base station.

Obtain the environmental parameters of dense urban areas, including building height distribution, average length and width, and density, establish a three-dimensional building blockage model, and obtain the distribution of the number of blocked buildings K' on the connection between the UAV base station and the user's three-dimensional space. The penetration loss factor is introduced, and the penetration loss S of the link between the user and the UAV base station is determined according to the distribution of the number of blocked buildings. Both the user's useful signal and the interference signal need to consider the impact of building blockage.

Based on the different occlusions between the user and the UAV base station link within the range of the UAV base station that the user can connect to, two types of users are given in Figure 1: users who can connect to the UAV base station and have UAVs with LOS paths Users who can connect to the UAV base station without LOS path UAV. For the two types of users shown in Figure 1, the corresponding UAV base station selection strategy is given according to the situation, including:

For users who can connect to UAV base stations with LOS-path UAVs, users can be served by the UAV base station beams of LOS paths, that is, there is no penetration loss of useful signals. The user selects the nearest LOS UAV base station as the serving base station.

For users who can connect to UAV base stations without LOS path UAVs, users can only be served by UAV base station beams with NLOS paths, that is, useful signals have penetration loss. If the signal passes through the building twice or more, the impact on the user is negligible. At this time, the user chooses the nearest UAV base station that is once blocked by the building as the serving base station.

Algorithm flow process of the present invention is as shown in accompanying drawing 2, and its concrete implementation steps are:

Step 300, determine the base station range of the drone that the user can connect to according to the deployment parameters of the drone and the antenna configuration.

Step 310, according to the acquired environmental parameters of the dense urban area, through three-dimensional space occlusion modeling, determine the occlusion of the link between any user and the UAV base station within the connectable range, and introduce the penetration loss factor to obtain the penetration of the link loss.

Step 320, according to the occlusion of the link between the user and the UAV base station within the connectable range determined above and the penetration loss of the link, select the UAV base station and determine the user service base station.

The simulation results are shown in Figure 3 and Figure 4, and the SIR coverage performance index of the network under the UAV base station selection scheme considering the occlusion effect of the present invention is studied. The SIR threshold is set to -5dB, the value range of the antenna angle is θ∈(0,π/2), the height of the UAV is 150m, and the average height of the building is 100m. In addition, the penetration loss factor in Figure 3 is set to 0.1, the UAV base station density in Figure 4 is set to 30/km ² , and the urban density p is 0.4. Based on the above simulation parameters, Figure 3 and Figure 4 study the relationship between network SIR coverage and antenna angle, UAV density, penetration loss factor, and urban density.

Figure 3 shows the relationship between the wide-beam UAV base station network coverage and the UAV antenna angle under different UAV densities and urban densities. It can be seen from the figure that: 1) When the UAV-related parameters and building-related parameters are determined, the beam coverage of the UAV base station increases first and then decreases with the change of the antenna angle of the UAV base station. The reason is that when the UAV deployment height is determined, the UAV beam pitch angle will become the only variable that affects the coverage of a single UAV beam. As the beam pitch angle increases, more users will be in the UAV base station. Within the beam coverage, when it increases to a certain limit and continues to increase, the increase in beam interference between UAVs will reduce the user's signal-to-interference ratio, resulting in a reduction in coverage. Therefore, in urban scenarios, when the density and deployment height of UAV base stations are determined, in order to improve the UAV group beam coverage, it is necessary to adjust the antenna angle of UAV base stations to a suitable angle. 2) The UAV density μ affects the optimal UAV base station antenna angle. The smaller the UAV density, the larger the UAV base station antenna angle to achieve the highest coverage. The reason is that when the drone density is small, a single drone needs a larger beam coverage to meet the coverage of all users. 3) The increase of urban density will lead to the reduction of UAV network coverage, and the optimal UAV antenna angle changes little when the UAV density is high (such as μ = 120/km ² ), when the UAV density Hours decrease more obviously with the increase of urban density (such as μ=30/km ² ). The reason is that when the UAV density is high, the coverage rate is less affected by the urban density, and its reduction is small; when the UAV density is low, the coverage rate is greatly affected by the buildings, which is also reflected in the most Optimal UAV antenna angle. When the UAV antenna angle increases to a certain value, continuing to increase the antenna angle will lead to a decrease in the user's signal-to-interference ratio, and the increase in urban density will affect the service UAV signal coverage, and the beam between UAV base stations will be affected. The interference is reduced, and the signal of the service drone is more seriously affected than when the urban density is small.

Fig. 4 describes the total coverage rate _Pc of the UAV base station of the present invention when different penetration loss factors and only consider the coverage rate _Pc1 when there is a LOS path UAV base station in the range of the UAV base station that the user can connect to. changes in the angle of the antenna. It can be seen from the figure: 1) Analysis of the influence of penetration loss factor: when γ = 0.1, the coverage rate is higher than that of γ = 0.5, when the drone density is sufficient to cover the limited urban area, the penetration loss factor increases While improving the coverage capability of a single UAV base station, it also increases the beam interference of other UAV base stations. At this time, the impact of the latter on the coverage rate leads to a decrease in the SIR value of most users, thereby reducing the coverage rate. 2) Comparative analysis of the total coverage P _c and the coverage P _c1 when only considering the LOS-path UAV base station within the range of the UAV base station that the user can connect to: Considering the LOS-path UAV and the UAV blocked by buildings There are two situations in which man-machine serves as a user to serve a UAV. When the coverage of a single UAV base station is small, as shown in Figure 4, when the UAV antenna angle is small (θ<1rad), consider the UAV base station blocked by buildings. Services to users will greatly increase coverage. 3) Comparative analysis of coverage change when γ=0: When the coverage of a single UAV base station is small, as shown in Figure 4, when the UAV antenna angle is small (θ<0.8rad), the present invention, that is, the penetration loss When it is not 0, the coverage rate is much greater than the coverage rate when γ=0, but as the coverage of a single UAV base station increases, the coverage rate of the present invention is less than the coverage rate when γ=0, and the coverage rate when γ=0 The peak rate may be higher than the peak coverage rate when γ>0. The reason is that when the coverage of a single UAV is limited, if the blocked UAV beam can serve users, the network coverage of the UAV base station will be greatly improved, but as the coverage of a single UAV base station increases Large, the UAV base station network is sufficient to cover the entire area, and there will be other UAVs serving users who were previously blocked by buildings and could not get the UAV base station beam service; when γ = 0, there is no UAV blocked by buildings The interference of the drone base station beam makes the coverage rate higher than the coverage rate in this chapter and the coverage peak may be larger when the coverage of a single drone base station is large enough.

Those of ordinary skill in the art should recognize that the above embodiments are only used to illustrate the present invention, rather than as a limitation of the present invention, as long as within the scope of the present invention, changes and modifications to the above embodiments will fall within the scope of the present invention. In the protection scope of the present invention.

Claims (3)

1. A method for selecting a UAV base station under the occlusion effect, it is characterized in that, comprising: the wide-beam UAV base station is deployed in a dense urban area at a height h from the ground, and the antenna angle is set to θ,

The scope of the wide-beam UAV base station that users can connect to is a circular area with the user as the center and a radius of htanθ; obtain the environmental parameters of dense urban areas, and establish a three-dimensional building blockage model according to the distribution parameters of urban buildings; introduce penetration loss Factor, which is the power loss ratio after the signal passes through the building, and the penetration loss factor is determined according to the beam model of the wide beam; the penetration loss is determined according to the blocking model and the penetration loss factor; according to the determined user and the UAV within the connectable range The occlusion of the link between the base stations and the penetration loss of the link are used to select the base station of the UAV. The selection scheme is that when there is a UAV base station with a LOS path within the user’s connectable range UAV base station beam service, the user selects the UAV base station with the largest RSRP as its serving base station; when there is no UAV base station with LOS path within the user’s connectable range htanθ, the user is served by the UAV base station beam with NLOS path, The user selects the nearest UAV base station that is once blocked by a building as the serving base station. 2. method according to claim 1, it is characterized in that, obtain dense urban environment parameter, comprise building position distribution, height distribution, average length and width, density, set up three-dimensional space building blocking model, obtain unmanned aerial vehicle base station and The distribution of the number of blocked buildings K' on the user's three-dimensional space connection, the expression is:

Among them, R is the distance from the user to the horizontal projection of the UAV base station, p is the normalized urban density obtained from the building density λ, β is a parameter related to the average length and width of the building and the building density, and η is the three-dimensional space The building blocking probability of is calculated as:

Among them, the upper limit of points

The building at the corresponding position on the horizontal projection line between the user and the UAV base station just blocks the channel height between the user and the UAV base station, and f _H (h _b ') is the height distribution function of the building. 3. The method according to claim 2, wherein the penetration loss factor γ is introduced, and the penetration loss S of the user and the UAV base station link is determined according to the distribution of the number of blocked buildings, and its calculation formula is: S = γ ^K' , Both the user's useful signal and the interference signal need to consider the impact of building blockage.

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