CN111970710B - A configuration method for UAV terminal to access cellular network - Google Patents

Abstract

The embodiment of the invention provides a configuration method for accessing an unmanned aerial vehicle terminal into a cellular network, which comprises the steps of estimating the features of a terrain and a link where an unmanned aerial vehicle user is located, collecting load and RSRP (reference signal received power) information of adjacent cells, and calculating an initial access cell, initial access height and initial access power of the unmanned aerial vehicle user; the method comprises the steps that an unmanned aerial vehicle user is taken as a center, and adjacent base stations periodically interact the interference condition and position information of a ground user service link in each cell; and carrying out periodic power control and height adjustment on the unmanned aerial vehicle user according to the interference condition and the position information of the adjacent cell ground user. The embodiment of the invention solves the problem of how to configure the flight height and the transmitting power of the unmanned aerial vehicle user in the process of accessing the 5G network to the unmanned aerial vehicle user so as to reduce the influence on the existing ground user link.

Description

A configuration method for UAV terminal to access cellular network

technical field

The present invention relates to the technical field of wireless communication, in particular to a method for configuring the transmission power and flight height of a drone user under the background that an existing ground 5G network supports the drone user.

Background technique

The rapid development of UAV technology has brought many industrialized applications: data collection, cargo transportation, rescue and disaster relief, etc. It is an important research direction to carry UAV data traffic through the existing ground wireless infrastructure.

However, due to the high-probability Line-of-Sight (LoS) link brought by the UAV hanging high, the access of the UAV to the existing ground wireless network will bring strong co-frequency to the existing ground users. Interference (mainly uplink).

Therefore, how to configure the UAV connected to the wireless network, adjust the flight height, control the transmission power, and reduce the co-channel interference to the existing ground users is an urgent problem to be solved.

SUMMARY OF THE INVENTION

The purpose of the present invention is to provide a configuration method for a UAV terminal to access a cellular network, so as to reduce the influence of the same-frequency interference of the UAV on the performance of existing ground users and improve the resource utilization rate. The specific technical solutions are as follows:

Step 200: Estimate the terrain and link characteristics of the UAV user, collect adjacent cell load and RSRP information, and calculate the initial access cell, initial access height and initial access power of the UAV user.

Step 210, with the UAV user as the center, the adjacent base stations periodically exchange the interference situation and location information of the service link of the ground user in each cell.

Step 220: Periodic power control and altitude adjustment are performed on the UAV user according to the interference situation and location information of the ground user in the adjacent cell.

Optionally, the terrain and link characteristics where the UAV user is located are estimated, the load and RSRP information of adjacent cells are collected, and the initial access cell, initial access height and initial access power of the UAV user are calculated, Specifically include:

According to the height distribution of buildings in the distribution area of UAV users, the building proportion (ie duty cycle), and the building density, the parameters to quantify the terrain features are calculated;

According to the spatial location of the drone user and the spatial location of the cell, combined with the cell RSRP, calculate the additional loss and attenuation coefficient of the drone link in the distribution area, and model the link characteristics of the drone user to the adjacent cell;

Calculate the initial access cell, initial access height and initial access power according to the spatial location, load situation and link characteristics of adjacent cells.

Optionally, according to the height distribution of buildings in the distribution area of UAV users, the construction ratio (that is, the duty ratio), and the building density, the parameters for calculating and quantifying the terrain features are calculated, specifically including:

Based on map data, with a single UAV as the center, calculate the average height, building space ratio, and building density of buildings within a radius of 5km;

Based on Monte Carlo simulation, simulate the characteristics of buildings in the UAV distribution area, where the height of the buildings obeys a negative exponential distribution, and based on the Poisson point process, the UAV user position and the ground base station position are randomly generated;

Based on the geometric relationship, calculate the occlusion of the UAV user-base station link;

Fit the LoS probability function P _LoS =1/(1+ae ^{-180b*arctan(h/r)/π+ab} ) to obtain the topographic quantitative feature parameters (a,b). In addition, h and r are the vertical and horizontal distances from the UAV user to the ground service site, respectively.

Optionally, the additional loss and attenuation coefficient of the UAV link in the distribution area are calculated according to the spatial location of the UAV user and the spatial location of the cell, combined with the cell RSRP, and the link from the UAV user to the adjacent cell is modeled. Road characteristics, including:

The path loss of the UAV-ground base station link is expressed as:

Among them, η _LoS and η _NLoS represent the additional loss of LoS link and NLoS link, respectively, α _LoS and α _NLoS represent the attenuation coefficient of LoS link and NLoS link, respectively;

According to the RSRP collected by the UAV user and the spatial geometric distance between the UAV user and the adjacent base station, the LoS/NLoS link is distinguished, and the path loss function is fitted to solve η _LoS , η _NLoS , α _LoS and α _NLoS .

Optionally, according to the RSRP collected by the drone user and the spatial geometric distance between the drone user and the adjacent base station, the LoS/NLoS link is distinguished, specifically including:

All UAV users in the area upload the RSRP of the adjacent base station and their own spatial coordinates;

Calculate the link propagation distance according to the spatial coordinates of the UAV user and the ground base station;

Based on the link propagation distance and RSRP parameters, a two-bit data set is constructed, and a clustering algorithm is used to distinguish LoS link data and NLoS link data.

Optionally, calculating the initial access cell, initial access height and initial access power according to the spatial position, load situation and link characteristics of the adjacent cells, specifically including:

The drone user selects the access cell according to the load situation and spatial location of the adjacent cell;

The UAV user determines the initial access height according to the horizontal distance from the access cell and the link attenuation characteristics;

The UAV user determines the initial access power according to the horizontal distance of the adjacent cell and the load of the adjacent cell.

Optionally, the drone user selects the access cell according to the load situation and spatial location of the adjacent cell, specifically including:

The probability of LoS transmission occurring in the link from the UAV user to the adjacent cell is expressed as: P _LoS =1/(1+ae ^{-180b*arctan(h/r)/π+ab} ), where h and r are no The vertical and horizontal distances of the human-machine user to the ground service site. Correspondingly, the probability of NLoS transmission is expressed as: P _NLoS =1-P _LoS ;

The average link attenuation from UAV users to adjacent cells is expressed as:

The occupancy weight attenuation function is constructed by combining the occupancy rate μ of the adjacent cell resource blocks and the average link attenuation: Lμ ^-β , the user selects the access cell with the largest value. Among them, β is the adjustment factor, which controls the weight of the occupancy rate.

Optionally, the UAV user determines the initial access height according to the horizontal distance from the access cell and link attenuation characteristics, specifically including:

According to the horizontal distance of the UAV user from the access cell, the function of the UAV user-ground base station link loss related to the hanging height of the UAV user is obtained, that is, L(h);

Based on the obtained functional relationship, the first-order pole is solved to obtain the initial access height with the minimum link loss of the UAV.

Optionally, the UAV user determines the initial access power according to the horizontal distance of the adjacent cell and the load of the adjacent cell, which specifically includes:

According to the horizontal distance and hanging height between the UAV user and the access cell, the LoS/NLoS status of the service link is determined, and then the specific link attenuation model is determined, that is,

UAV users adopt partial inversion power control based on path loss, that is, P=ρL ^-ε , where ε represents the power inversion coefficient for UAV users, which is inversely related to the load degree of the adjacent area, and ρ is the received power adjustment factor.

Optionally, according to the interference situation and location information of ground users in adjacent cells, periodic power control and height adjustment are performed on the drone users, specifically including:

和没有无人机用户接入情况下的地面用户平均覆盖率

Taking the drone users as the center, calculate the average coverage of ground users in adjacent cells

and the average coverage of ground users without UAV user access

If P _c '≤τP _c , take Δh as the benchmark, gradually adjust the hanging height of the UAV user until P _c '>τP _c , where τ is the tolerance of ground user performance loss;

If the basic service performance of ground users cannot be guaranteed by adjusting the height, the power reversal coefficient τ of UAV users is gradually reduced based on 0.01, and its value range is (0.9, 1].

和没有无人机用户接入情况下的地面用户平均覆盖率

具体包括：Optionally, the average coverage rate of ground users in adjacent cells is calculated with the drone user as the center

and the average coverage of ground users without UAV user access

Specifically include:

Obtain the spatial positions of all UAV users and ground users in the area, and calculate the propagation distance of the interference link of the ground user service site;

For the UAV user interference link, the small-scale fading is modeled as Nakagami-m distribution; for the ground user interference link, the small-scale fading is modeled as Rayleigh distribution;

S_t表示地面用户上行接收功率，I_a和I_t分别表示无人机用户和地面用户带来的同频干扰；Calculate the probability density distribution function P _c =P(SIR>T) of the uplink signal-to-noise ratio of terrestrial users, where the user's signal-to-noise ratio is expressed as:

S _t represents the uplink received power of the ground user, and I _a and It represent the co-channel interference caused by the UAV user and the ground user _, respectively;

With a fixed threshold (T=-10, 0, 10dB), the average coverage rate of all ground users in the central area is calculated as the UAV user, namely

Similar to the above process, remove the interference link of UAV users in the SIR, and calculate the average coverage of ground users when there is no UAV user access

Optionally, if P _c '≤τP _c , take Δh as the benchmark, gradually adjust the hanging height of the UAV user until P _c '>τP _c , where τ is the tolerance of ground user performance loss, specifically: include:

Calculate the regional centroid of the distribution area of UAV users, and start from the UAV user who is farthest from the centroid to adjust the height and power of the UAV;

For the top 50% of drone users, gradually increase their access altitude until the requirements are met;

For the last 50% of drone users, gradually reduce their access altitude until the requirements are met.

Optionally, if the basic service performance of the ground user cannot be guaranteed by adjusting the height, the power inversion coefficient τ of the UAV user is gradually reduced based on 0.01, and its value range is (0.9, 1], which specifically includes:

During the height adjustment process of the UAV user, if the performance requirements of the ground user cannot be met, the power inversion coefficient of the UAV user will be reduced by 0.01;

Based on the initial access height, re-adjust the drone user's hanging height. If the requirements still cannot be met, go back to the previous step.

beneficial effect

It can be seen from the above that the configuration method for the access of the drone terminal to the cellular network provided by the present invention is to set the initial access cell, the initial access height and the initial access power of the drone user. After that, according to the performance changes of the ground users in the adjacent cells, the hanging height and transmit power of the drone users will be adjusted, so as to effectively reduce the co-channel interference to the existing ground users, and provide the drone users in the air. High rate service.

Description of drawings

1 is a system model diagram of a configuration method for an unmanned aerial vehicle terminal to access a cellular network according to the present invention;

Fig. 2 is the algorithm implementation flow chart of the present invention;

Figure 3 is a schematic diagram of the coverage rate of drone users and ground users changing with the height of the drone;

Fig. 4 is a schematic diagram of the variation of the coverage ratio of UAV users and ground users with the power reversal factor;

Detailed ways

In order to clarify the purpose, embodiments and technical advantages of the present invention, the present invention will be further described in detail below with reference to specific embodiments and accompanying drawings.

1 is a practical application scenario of a configuration method for a UAV terminal to access a cellular network according to the present invention: as a ground cellular network user, the UAV unloads data traffic through a ground base station, and its uplink will cause damage to ground users at the same time. Serious co-channel interference. The present invention aims to configure UAV users accessing the ground network and reduce their impact on the performance of existing ground users.

2 is a schematic flowchart of a configuration method for a UAV terminal to access a cellular network provided by the present invention, including:

Step 200: Estimate the terrain and link characteristics of the UAV user, collect adjacent cell load and RSRP information, and calculate the initial access cell, initial access height and initial access power of the UAV user.

Step 210, with the UAV user as the center, the adjacent base stations periodically exchange the interference situation and location information of the service link of the ground user in each cell.

Step 220: Periodic power control and altitude adjustment are performed on the UAV user according to the interference situation and location information of the ground user in the adjacent cell.

In step 200, the estimation of terrain and link characteristics needs to utilize the spatial characteristics of buildings in the area, which are specifically expressed as: height distribution, spatial density, duty cycle and geometric shape. It can be extracted from map information.

In step 210, with the UAV user as the center, when the adjacent base station periodically exchanges the co-frequency interference situation and location information of the service link of the ground user in each cell, the interaction period of the interference situation and the location information may be different. For example, the interaction period of the location information can be an integer multiple of the interaction period of the interference situation, the change degree of the location information of the ground user is much smaller than the channel change period, and the related calculation results can be reused for a long time. After each interaction with the interference situation, the UAV user can quickly obtain the relevant parameters for adjusting its own height and transmit power based on the calculation results of the previous position information, so as to quickly ensure the service performance of the ground users.

In step 220, the adjustment period for the user power and the hanging height of the UAV may be synchronous or asynchronous. For example, for an area with large changes in terrain features, it is necessary to periodically calculate and set terrain parameters (step 210), and the interference level of the ground user of the drone user will fluctuate at an accelerated rate. Synchronous adjustment; for areas with small changes in terrain features, the power adjustment period can be an integer multiple of the height adjustment period.

It can be seen from the above that the method for configuring a drone terminal to access a cellular network provided by the present invention, after obtaining the initial access cell, initial access height and initial access power of the drone user, also According to the change of the link status and spatial position of the ground user in the adjacent cell of the drone user, the hanging height and transmission power of the drone user will be adjusted in real time, so as to ensure the basic service performance of the ground user and provide high-quality drone users. speed connection.

In some optional embodiments, in step 200, the terrain and link characteristics of the drone user are estimated, the load and RSRP information of adjacent cells are collected, and the initial access cell and initial access altitude of the drone user are calculated. and initial access power, including:

Step 310, according to the height distribution of the buildings in the UAV user distribution area, the construction ratio (that is, the duty cycle), and the construction density, calculate the parameters for quantifying the terrain features;

Step 320, according to the spatial location of the drone user and the spatial location of the cell, combined with the cell RSRP, calculate the additional loss and attenuation coefficient of the drone link in the distribution area, and model the link characteristic of the drone user to the adjacent cell;

Step 330: Calculate the initial access cell, the initial access height and the initial access power according to the spatial position, load condition and link characteristics of the adjacent cells.

Preferably, in another optional embodiment, in step 310, according to the height distribution of the buildings in the distribution area of the drone users, the construction ratio (that is, the duty cycle), and the building density, the parameters for quantifying the terrain features are calculated. , including:

Step 400, based on the map data, with a single UAV as the center, calculate the average height, building space ratio, and building density of buildings within a radius of 5km;

Step 410, based on the Monte Carlo simulation, simulate the characteristics of buildings in the distribution area of the UAV, wherein the height of the buildings obeys a negative exponential distribution, and based on a Poisson point process, the location of the UAV user and the location of the ground base station are randomly generated;

Step 420, based on the geometric relationship, calculate the occlusion situation of the UAV user-base station link;

Step 430: Fit the LoS probability function P _LoS =1/(1+ae ^{-180b*arctan(h/r)/π+ab} ) proposed in "Optimal LAP Altitude for Maximum Coverage" to obtain the terrain quantitative feature parameter (a ,b). In addition, h and r are the vertical and horizontal distances from the UAV user to the ground service site, respectively.

In step 400, the calculation radius can be adjusted, preferably 1/2 to 1/8 of the square root of the area of the entire UAV user distribution area. In order to achieve a better fitting degree of the statistical model, the larger the calculation range, the better. At the same time, in order to reduce the calculation amount, the data collection range can be appropriately reduced.

In step 410, a traditional Manhattan block model can be used to simulate the distribution of buildings, wherein the buildings are modeled as cuboids and distributed horizontally on a grid-like map. For areas with cluttered building distribution characteristics, it is necessary to adjust the distribution of buildings in Monte Carlo simulation.

Preferably, in another optional embodiment, in step 320, according to the spatial location of the drone user and the spatial location of the cell, combined with the cell RSRP, calculate the additional loss and attenuation coefficient of the drone link in the distribution area, Model the link characteristics of UAV users to adjacent cells, including:

In step 500, the path loss of the UAV-ground base station link is expressed as:

Among them, η _LoS and η _NLoS represent the additional loss of LoS link and NLoS link, respectively, α _LoS and α _NLoS represent the attenuation coefficient of LoS link and NLoS link, respectively;

Step 510, according to the RSRP collected by the drone user and the spatial geometric distance between the drone user and the adjacent base station, distinguish the LoS/NLoS link, fit the path loss function, and solve η _LoS , η _NLoS , α _LoS and α _NLoS .

Preferably, in another optional embodiment, in step 510, distinguish LoS/NLoS links, and fit a path loss function, which specifically includes:

Step 600, all UAV users in the area upload the RSRP of the adjacent base station and their own spatial coordinates;

Step 610: Calculate the link propagation distance according to the spatial coordinates of the drone user and the ground base station;

In step 620, a two-bit data set is constructed based on the link propagation distance and RSRP parameters, and a clustering algorithm is used to distinguish LoS link data and NLoS link data.

Preferably, in another optional embodiment, in step 330, the initial access cell, the initial access height and the initial access power are calculated according to the spatial position, load condition and link characteristics of the adjacent cells, specifically: include:

Step 700, the drone user selects the access cell according to the load situation and spatial location of the adjacent cell;

Step 710, the drone user determines the initial access height according to the horizontal distance from the access cell and the link attenuation characteristics;

In step 720, the UAV user determines the initial access power according to the horizontal distance of the adjacent cell and the load of the adjacent cell.

Preferably, in another optional embodiment, in step 700, the drone user selects the access cell according to the load situation and spatial position of the adjacent cell, which specifically includes:

In step 800, the probability of LoS transmission occurring in the link from the drone user to the adjacent cell is expressed as: P _LoS =1/(1+ae- ^{180b*arctan(h/r)/π+ab} ), where h and r are the vertical and horizontal distances from the UAV user to the ground service station, respectively. Correspondingly, the probability of NLoS transmission is expressed as: P _NLoS =1-P _LoS ;

Step 810, the average link attenuation of the drone user to the adjacent cell is expressed as:

Step 820, combining the occupancy rate μ of adjacent cell resource blocks and the average link attenuation to construct an occupancy rate weight decay function: Lμ ^-β , the user selects the access cell with the largest value. Among them, β is the adjustment factor, which controls the weight of the occupancy rate.

Preferably, in another optional embodiment, in step 710, the drone user determines the initial access height according to the horizontal distance from the access cell and the link attenuation characteristics, which specifically includes:

Step 900, according to the horizontal distance of the UAV user from the access cell, obtain a function of the UAV user-ground base station link loss related to the hanging height of the UAV user, namely L(h);

Step 910, based on the obtained functional relationship, solve the first-order pole to obtain the initial access height with the smallest link loss of the UAV.

Optionally, in step 900, L(h) usually adopts the probability average propagation loss function provided in step 810. Before determining the initial height, if the spatial geometric characteristics of the main link occluders are known, the LoS/NLoS propagation model provided in step 500 can be used to solve the optimal solutions under LoS and NLoS conditions respectively, and finally select the links in the two solutions. The solution with the least attenuation.

Preferably, in another optional embodiment, in step 720, the drone user determines the initial access power according to the horizontal distance of the adjacent cell and the load of the adjacent cell, which specifically includes:

Step 1010, determine the LoS/NLoS status of the service link according to the horizontal distance and the hanging height of the drone user and the access cell, and then determine a specific link attenuation model, that is, the link model given in step 500;

Step 1020, the UAV user adopts partial inversion power control based on path loss, that is, P=ρL- ^ε , where ε represents the power inversion coefficient for the UAV user, which is inversely related to the load degree of the adjacent area, and ρ is Received power adjustment factor.

In step 1010, the UAV user has obtained the RSRP of the access cell, and according to the calculated link propagation distance, combined with the link model in step 500, the model fading coefficient is obtained, and the link fading coefficient estimated by RSRP is compared. Determine the link LoS/NLoS type.

Preferably, in another optional embodiment, in step 220, according to the interference situation and location information of the ground users in the adjacent cell, periodic power control and altitude adjustment are performed on the drone users, specifically including:

和没有无人机用户接入情况下的地面用户平均覆盖率

Step 1110, with the drone user as the center, calculate the average coverage rate of the ground users in the adjacent cell

and the average coverage of ground users without UAV user access

Step 1120, if P _c '≤τP _c , take Δh as the benchmark, gradually adjust the hanging height of the UAV user until P _c '>τP _c , where τ is the tolerance of ground user performance loss;

Step 1130, if the basic service performance of the ground user cannot be guaranteed by adjusting the height, the power inversion coefficient τ of the UAV user is gradually reduced based on 0.01, and its value range is (0.9, 1].

和没有无人机用户接入情况下的地面用户平均覆盖率

具体包括：Preferably, in another optional embodiment, in step 1110, taking the drone user as the center, calculate the average coverage rate of the ground users in the adjacent cell

and average coverage of ground users without UAV user access

Specifically include:

Step 1210: Obtain the spatial positions of all UAV users and ground users in the area, and calculate the propagation distance of the interference link of the ground user service site;

Step 1220, for the UAV user interference link, its small-scale fading is modeled as Nakagami-m distribution; for the ground user interference link, its small-scale fading is modeled as Rayleigh distribution;

S_t表示地面用户上行接收功率，I_a和I_t分别表示无人机用户和地面用户带来的同频干扰；Step 1230: Calculate the probability density distribution function P _c =P(SIR>T) of the terrestrial user uplink signal-to-noise ratio, where the user's signal-to-noise ratio is expressed as:

S _t represents the uplink received power of the ground user, and I _a and It represent the co-channel interference caused by the UAV user and the ground user _, respectively;

Step 1240, fix the threshold (T=-10, 0, 10dB), and calculate the average coverage rate of all ground users in the central area where the drone users are, that is,

Step 1250, similar to the above process, remove the interference link of UAV users in the SIR, and calculate the average coverage rate of ground users when there is no UAV user access

Optionally, in step 1220, the LoS/NLoS category of the link between the UAV user and the ground base station can be determined by comparing the fading coefficient obtained by bringing the propagation distance into the propagation model in step 500 and the fading coefficient estimated by RSRP. Furthermore, Nakagami-m distribution is used to model small-scale fading for LoS links, and Rayleigh fading is used for NLoS links to model small-scale fading.

Preferably, in another optional embodiment, in step 1120, if P _c '≤τP _c , take Δh as the benchmark, gradually adjust the hanging height of the drone user until P _c '>τP _c is satisfied, wherein τ is the tolerance of ground user performance loss, which includes:

Step 1300: Calculate the regional centroid of the UAV user distribution area, and adjust the UAV hanging height and power from the UAV user farthest from the centroid;

Step 1310, for the first 50% of the drone users, gradually increase the access height until the requirements are met; for the last 50% of the drone users, gradually reduce the access height until the requirements are met.

Preferably, in another optional embodiment, in step 1130, if the basic service performance of the ground user cannot be guaranteed by adjusting the height, the power inversion coefficient τ of the drone user is gradually reduced based on 0.01, which is The value range is (0.9,1], which includes:

Step 1400, in the process of adjusting the height of the drone user, if the performance requirements of the ground user cannot be met, reduce the power inversion coefficient of the drone user by 0.01;

Step 1410, re-adjust the height of the drone user based on the initial access height, and return to the previous step if the requirement still cannot be met.

Figure 3 is the intention of the coverage rate of drone users and ground users changing with the height of the drone. The coverage rate represents the statistical probability that the SIR of the user service link meets the standard under a certain SIR threshold requirement. The horizontal axis represents the height of the drone user. The simulation results show the effect of adjusting the height of UAV users on the performance of ground users and UAV users under different cell densities. It can be seen that under the reverse power control, there are two optimal height deployment intervals for UAV users; for dense network scenarios, more precise height adjustment is required to ensure the basic performance of ground users.

Figure 4 is a plot of UAV user and ground user coverage as a function of power reversal factor. In step 1120, referring to FIG. 3, adjusting the height of the drone user within a certain range may not guarantee the service quality of the ground user. It is necessary to appropriately reduce the UAV user power inversion coefficient in combination with Figure 4, thereby improving the performance of the ground user link.

Claims (9)

1. a configuration method for unmanned aerial vehicle terminal access cellular network, is characterized in that, comprises: Estimate the terrain and link characteristics of the UAV user, collect the load and RSRP information of adjacent cells, and calculate the initial access cell, initial access height and initial access power of the UAV user: according to the distribution of UAV users The height distribution and construction ratio of buildings in the area, that is, the duty cycle and building density, calculate the parameters that quantify the terrain features; according to the spatial location of the drone user and the spatial location of the cell, combined with the cell RSRP, calculate the unmanned person in the distribution area. The additional loss and attenuation coefficient of the drone link are used to model the link characteristics of the drone user to the adjacent cell; the initial access cell, initial access height and initial access power; Taking the UAV user as the center, the adjacent base stations periodically exchange the interference situation and location information of the service link of the ground user in each cell; Periodic power control and altitude adjustment for UAV users according to the interference situation and location information of ground users in adjacent cells; According to the interference situation and location information of the ground users in the adjacent cells, periodic power control and height adjustment are performed on the UAV users, which specifically includes: taking the UAV users as the center, calculating the average coverage rate of the ground users in the adjacent cells.

and the average coverage of ground users without UAV user access

like

Based on △h, gradually adjust the hanging height of the drone user until it meets the

Among them, τ is the tolerance of ground user performance loss. If the basic service performance of ground users cannot be guaranteed by adjusting the height, the power inversion coefficient τ of UAV users is gradually reduced based on 0.01, and its value range is (0.9, 1] ; The average coverage rate of ground users in adjacent cells is calculated with the drone users as the center.

and the average coverage of ground users without UAV user access

Specifically include: Obtain the spatial positions of all UAV users and ground users in the area, and calculate the propagation distance of the interference link of the ground user service site; for the UAV user interference link, the small-scale fading is modeled as Nakagami-m distribution; The user interferes with the link, and its small-scale fading is modeled as a Rayleigh distribution, and the probability density distribution function of the uplink signal-to-noise ratio of the ground user is calculated, where the user's signal-to-noise ratio is expressed as:

S _t represents the uplink received power of the ground user, I _a and It represent the co-channel interference caused by the UAV user and the ground user _, respectively, with a fixed threshold, namely T=-10, 0, 10dB, and the UAV user is the center of the calculation The average coverage of all ground users in the area, i.e.

Similar to the above process, remove the interference link of UAV users in the SIR, and calculate the average coverage of ground users when there is no UAV user access

2. method according to claim 1, is characterized in that, described according to the height distribution of buildings in the UAV user distribution area, construction ratio, namely duty ratio, construction density, calculate the parameter that quantifies terrain feature, Specifically include: Based on map data, with a single UAV as the center, calculate the average height of buildings in a fixed radius area, the proportion of building space, and the density of buildings; Based on Monte Carlo simulation, simulate the characteristics of buildings in the UAV distribution area, where the height of the buildings obeys a negative exponential distribution, and based on the Poisson point process, the UAV user position and the ground base station position are randomly generated; Based on the geometric relationship, calculate the occlusion of the UAV user-base station link; Fit the LoS probability function P _LoS =1/(1+ae ^{-180b*arctan(h/r)/π+ab} ) to obtain the terrain quantitative feature parameters (a,b), in addition, h and r are the UAV The vertical and horizontal distance of the user to the ground service site. 3. method according to claim 1, is characterized in that, described according to the space position of unmanned aerial vehicle user and cell space position, in conjunction with cell RSRP, calculate the additional loss and attenuation coefficient of unmanned aerial vehicle link in the distribution area, Model the link characteristics of UAV users to adjacent cells, including: The path loss of the UAV-ground base station link is expressed as:

Among them, η _LoS and η _NLoS represent the additional loss of LoS link and NLoS link, respectively, α _LoS and α _NLoS represent the attenuation coefficient of LoS link and NLoS link, respectively, h and r are UAV users to the ground service the vertical and horizontal distances of the site; According to the RSRP collected by the UAV user and the spatial geometric distance between the UAV user and the adjacent base station, the LoS/NLoS link is distinguished, and the path loss function is fitted to solve η _LoS , η _NLoS , α _LoS and α _NLoS . 4. The method according to claim 1, wherein calculating the initial access cell, initial access height and initial access power according to the spatial position, load condition and link characteristics of the adjacent cells, specifically comprising: The drone user selects the access cell according to the load situation and spatial location of the adjacent cell; The UAV user determines the initial access height according to the horizontal distance from the access cell and the link attenuation characteristics; The UAV user determines the initial access power according to the horizontal distance of the adjacent cell and the load of the adjacent cell. 5. The method according to claim 4, wherein the drone user selects the access cell according to the load situation of the adjacent cell and the spatial position, specifically comprising: The probability of LoS transmission occurring in the link from the UAV user to the adjacent cell is expressed as: P _LoS =1/(1+ae ^{-180b*arctan(h/r)/π+ab} ), where h and r are no The vertical distance and the horizontal distance from the human-machine user to the ground service site; correspondingly, the probability of NLoS transmission is expressed as: P _NLoS =1-P _LoS ; The average link attenuation from UAV users to adjacent cells is expressed as:

The occupancy weight attenuation function is constructed by combining the occupancy rate μ of the adjacent cell resource block and the average link attenuation: Lμ ^-β , the user selects the largest value as the access cell, where β is the adjustment factor, which controls the weight of the occupancy rate. 6. The method according to claim 4, wherein the UAV user determines the initial access height according to the horizontal distance from the access cell and the link attenuation characteristic, specifically comprising: According to the horizontal distance of the UAV user from the access cell, the function of the UAV user-ground base station link loss related to the hanging height of the UAV user is obtained, that is, L(h); Based on the obtained functional relationship, the first-order pole is solved to obtain the initial access height with the smallest link loss of the UAV. 7. The method according to claim 4, wherein the drone user determines the initial access power according to the horizontal distance of the adjacent cell and the load of the adjacent cell, specifically comprising: According to the horizontal distance and hanging height between the UAV user and the access cell, the LoS/NLoS status of the service link is determined, and then the specific link attenuation model is determined, that is,

Among them, η _LoS and η _NLoS represent the additional loss of LoS link and NLoS link, respectively, α _LoS and α _NLoS represent the attenuation coefficient of LoS link and NLoS link, respectively, h and r are UAV users to ground service the vertical and horizontal distances of the site; UAV users adopt partial inversion power control based on path loss, that is, P=ρL ^-ε , where ε represents the power inversion coefficient for UAV users, which is inversely related to the load degree of the adjacent area, and ρ is the received power adjustment factor. 8. The method of claim 1, wherein the if

Based on Δh, gradually adjust the hanging height of the drone user until it meets the

where τ is the tolerance of ground user performance loss, including: Calculate the regional centroid of the distribution area of UAV users, and adjust the height and power of the UAV from the UAV user who is farthest from the centroid; For the top 50% of drone users, gradually increase their access altitude until the requirements are met; For the last 50% of drone users, gradually reduce their access altitude until the requirements are met. 9. The method according to claim 1, wherein, if the basic service performance of ground users cannot be guaranteed by adjusting the height, the power reversal coefficient τ of the drone user is gradually reduced based on 0.01, and its value range is (0.9,1], including: In the process of adjusting the height of the UAV user, if the performance requirements of the ground user cannot be met, the power inversion coefficient of the UAV user will be reduced by 0.01; Based on the initial access height, re-adjust the drone user's hanging height. If the requirements still cannot be met, go back to the previous step.

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