Air-ground wireless network deployment method, device, equipment, medium and program product

Abstract

The invention provides an air-ground wireless network deployment method, device and equipment, a medium and a program product, and relates to the technical field of wireless communication. The method comprises the following steps: determining the number of air base stations in the air-to-ground wireless network and the positions of a plurality of ground user terminals required to be covered by the air-to-ground wireless network; based on the number of the base stations and the position of each ground user terminal, performing clustering processing on the plurality of ground user terminals to obtain a plurality of clusters; respectively determining the initial position of each air base station based on the central position of the position area represented by each cluster; and based on the initial position of each air base station, solving the optimization problem to obtain the deployment position of each air base station. According to the method, the influence of burst flow caused by dynamic change of user positions in a disaster scene on the network and the condition of dynamic change of interference are fully considered, and the ground user terminals are clustered by adopting clustering so as to reasonably deploy the positions of air base stations, so that the coverage integrity of the air-ground wireless network is improved.

Description

Technical Field

[0001] The present invention relates to the field of wireless communication technologies, and in particular, to a method, device, equipment, medium, and program product for deploying an air-ground wireless network. Background Art

[0002] In a disaster emergency scenario, ground base stations may be damaged, resulting in some ground base stations being unable to provide services normally. Therefore, it is necessary to provide more flexible and reliable air base stations to provide emergency rescue communication. Among them, air base stations can quickly provide communication services for ground user terminals in a disaster emergency scenario and quickly restore ground communication, but this requires reasonable deployment of air base stations.

[0003] Currently, an air-ground wireless network access and backhaul integrated system is established, and then the optimal deployment location of the air base station is determined according to the received signal-to-noise ratio of the air base station. However, the prior art does not consider the particularity of the disaster emergency scenario, that is, it does not consider the impact of damaged ground base stations that cannot provide services, which may lead to coverage holes and ultimately poor communication for ground users. Summary of the Invention

[0004] The present invention provides a method, device, equipment, medium, and program product for deploying an air-ground wireless network to solve the defect of poor communication for ground users in the prior art and achieve the coverage integrity of the air-ground wireless network.

[0005] The present invention provides a method for deploying an air-ground wireless network, including: Determining the number of base stations of air base stations in the air-ground wireless network and the positions of a plurality of ground user terminals to be covered by the air-ground wireless network; the air-ground wireless network includes a plurality of air base stations and a plurality of ground base stations that can provide services; Based on the number of base stations and the positions of the ground user terminals, performing clustering processing on the plurality of ground user terminals to obtain a plurality of clustering clusters; the number of the plurality of clustering clusters is the same as the number of base stations; Based on the central positions of the location areas represented by the clustering clusters, respectively determining the initial positions of the air base stations; Based on the initial positions of the air base stations, solving an optimization problem to obtain the deployment positions of the air base stations; the objective function of the optimization problem is used to maximize the total rate of ground user terminals, the total rate is the sum of the total data transmission rates of the ground user terminals, and the total data transmission rate of any ground user terminal is the sum of the data transmission rates provided by the associated base stations associated with the ground user terminal, and any associated base station is a base station associated with the ground user terminal in the air-ground wireless network, and the base station associated with the ground user terminal is used to provide services for the ground user terminal.

[0006] According to an air - ground wireless network deployment method provided by the present invention, solving an optimization problem to obtain the deployment positions of the air - base stations based on the initial positions of the air - base stations includes: Based on the initial positions of the air - base stations, using convex optimization to solve the optimization problem to obtain user association variables and the transmission powers of the base stations in the air - ground wireless network; the user association variables are used to characterize the association situations of the ground user terminals with the base stations in the air - ground wireless network respectively; Based on the user association variables and the transmission powers of the base stations in the air - ground wireless network, solve the optimization problem to obtain the deployment positions of the air - base stations.

[0007] According to an air - ground wireless network deployment method provided by the present invention, the method of solving the optimization problem to obtain the deployment positions of the air - base stations based on the user association variables and the transmission powers of the base stations in the air - ground wireless network includes: Based on the user association variables and the transmission powers of the base stations in the air - ground wireless network, determine the solution space of the optimization problem; Randomly initialize the positions of the particles in the particle swarm in the solution space, and determine the initial annealing temperature based on the difference between the maximum fitness value and the minimum fitness value of the particle swarm; the maximum fitness value is the maximum value among the fitness values of the particles in the particle swarm, and the minimum fitness value is the minimum value among the fitness values of the particles in the particle swarm; For each particle in the particle swarm, set the local optimal solution of the particle to the current position of the particle, and determine the global optimal solution based on the local optimal solutions of the particles in the particle swarm; If it is determined that the global optimal solution still needs to be updated, for any particle in the particle swarm, update the position and velocity of the particle. If the fitness value of the particle is better than the fitness value of the local optimal solution of the particle, update the local optimal solution of the particle to the current position of the particle. If the fitness value of the particle is better than the fitness value of the global optimal solution, update the global optimal solution to the current position of the particle; Randomly generate a new position for the particle; If the fitness value of the particle at its current position is less than the fitness value of the particle at the new position, update the current position of the particle to the new position and reduce the annealing temperature; If the fitness value of the particle at its current position is greater than or equal to the fitness value of the particle at the new position, and it is determined based on the annealing temperature to update the current position of the particle to the new position, reduce the annealing temperature, and return the step of, if the fitness value of the particle is better than the fitness value of the local optimal solution of the particle, updating the local optimal solution of the particle to the current position of the particle, and if the fitness value of the particle is better than the fitness value of the global optimal solution, updating the global optimal solution to the current position of the particle; If it is determined that the global optimal solution still needs to be updated, return the step of updating the position and velocity of the particle; If it is determined that the global optimal solution does not need to be updated, obtain the deployment positions of the air base stations based on the global optimal solution.

[0008] According to an air-ground wireless network deployment method provided by the present invention, the fitness value is determined based on the target number of ground user terminals and the target number of air base stations; The target number of ground user terminals is the number of ground user terminals among the multiple ground user terminals whose received signal-to-noise ratio of the access link is lower than the first target received signal-to-noise ratio; The target number of air base stations is the number of air base stations among the multiple air base stations whose received signal-to-noise ratio of the backhaul link is lower than the second target received signal-to-noise ratio.

[0009] According to an air-ground wireless network deployment method provided by the present invention, the step of, if the fitness value of the particle at its current position is greater than or equal to the fitness value of the particle at the new position, and it is determined based on the annealing temperature to update the current position of the particle to the new position, reduce the annealing temperature, and return the step of, if the fitness value of the particle is better than the fitness value of the local optimal solution of the particle, updating the local optimal solution of the particle to the current position of the particle, and if the fitness value of the particle is better than the fitness value of the global optimal solution, updating the global optimal solution to the current position of the particle, includes: If the fitness value of the particle at its current position is greater than or equal to the fitness value of the particle at the new position, generate a random number within a preset value range; Based on the annealing temperature and the fitness difference between the fitness value of the particle at its current position and the fitness value of the particle at the new position, determine an update threshold; Determine that the random number is less than the update threshold, update the current position of the particle to the new position, lower the annealing temperature, and return the step of updating the local optimal solution of the particle to the current position of the particle if the fitness value of the particle is better than the fitness value of the local optimal solution of the particle, and updating the global optimal solution to the current position of the particle if the fitness value of the particle is better than the fitness value of the global optimal solution.

[0010] According to an air-ground wireless network deployment method provided by the present invention, after solving an optimization problem based on the user association variable and the transmission power of each base station in the air-ground wireless network to obtain the deployment positions of each of the aerial base stations, the method further includes: Based on the deployment positions of each of the aerial base stations, use a convex optimization method to solve the optimization problem to obtain an updated user association variable and updated transmission power of each base station in the air-ground wireless network.

[0011] According to an air-ground wireless network deployment method provided by the present invention, the user association variable includes a plurality of binary association variables, and any one of the binary association variables is used to represent the association situation between a ground user terminal and a base station in the air-ground wireless network; The step of solving an optimization problem based on the initial positions of each of the aerial base stations by using a convex optimization method to obtain a user association variable and the transmission power of each base station in the air-ground wireless network includes: Relax the binary association variable; Based on the initial positions of each of the aerial base stations, use a convex optimization method to solve the optimization problem to obtain an initial user association variable and the transmission power of each base station in the air-ground wireless network; Round each binary association variable in the initial user association variable to obtain a user association variable.

[0012] According to an air-ground wireless network deployment method provided by the present invention, the constraint conditions of the optimization problem include a first user association constraint condition; The first user association constraint condition is used to constrain that a delay-sensitive ground user terminal can only be associated with a ground base station.

[0013] According to an air-ground wireless network deployment method provided by the present invention, the constraint conditions further include a signal-to-noise ratio constraint condition, a second user association constraint condition, an access rate constraint condition, a base station transmission power constraint condition, and an aerial base station position constraint condition; The signal-to-noise ratio constraint condition is used to constrain that the received signal-to-noise ratio of each of the ground user terminals is not less than a preset received signal-to-noise ratio threshold; The second user association constraint condition is used to constrain that a ground user terminal can only be associated with one base station; The access rate constraint condition is used to ensure that the access rate provided by each of the aerial base stations to the ground user terminals does not exceed the backhaul rate of the aerial base station; the access rate provided by any one of the aerial base stations to the ground user terminals is the sum of the data rates received by each of the ground user terminals from the aerial base station, and the backhaul rate of the aerial base station is determined based on the backhaul capacity provided by the satellite to the aerial base station and the backhaul capacity provided by the ground base station associated with the aerial base station; The base station transmission power constraint condition is used to ensure that the transmission power of each base station in the air-ground wireless network does not exceed its maximum transmission power; The aerial base station location constraint condition is used to restrict the deployment areas of each of the aerial base stations.

[0014] The present invention also provides an air-ground wireless network deployment device, including: A number determination module, configured to determine the number of base stations of the aerial base stations in the air-ground wireless network, and the locations of a plurality of ground user terminals to be covered by the air-ground wireless network; the air-ground wireless network includes a plurality of aerial base stations and a plurality of ground base stations that can provide services; A user clustering module, configured to perform clustering processing on the plurality of ground user terminals based on the number of base stations and the locations of each of the ground user terminals, to obtain a plurality of clustering clusters; the number of the plurality of clustering clusters is the same as the number of base stations; A location determination module, configured to respectively determine the initial locations of each of the aerial base stations based on the central locations of the location regions represented by each of the clustering clusters; A location solution module, configured to solve an optimization problem based on the initial locations of each of the aerial base stations to obtain the deployment locations of each of the aerial base stations; the objective function of the optimization problem is used to maximize the total rate of the ground user terminals, the total rate is the sum of the total data transmission rates of each of the ground user terminals, and the total data transmission rate of any one of the ground user terminals is the sum of the data transmission rates provided by each associated base station associated with the ground user terminal, and any one of the associated base stations is a base station associated with the ground user terminal in the air-ground wireless network, and the base station associated with the ground user terminal is used to provide services to the ground user terminal.

[0015] The present invention also provides an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor, and when the processor executes the program, it implements any one of the above-mentioned air-ground wireless network deployment methods.

[0016] The present invention also provides a non-transitory computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, it implements any one of the above-mentioned air-ground wireless network deployment methods.

[0017] The present invention also provides a computer program product, including a computer program, which when executed by a processor implements the method for deploying an air-ground wireless network as described in any one of the above.

[0018] The method, device, equipment, medium and program product for deploying an air-ground wireless network provided by the present invention determine the number of base stations of the air base stations in the air-ground wireless network and the positions of a plurality of ground user terminals to be covered by the air-ground wireless network. The air-ground wireless network includes a plurality of air base stations and a plurality of ground base stations that can provide services. Based on the number of base stations and the positions of each ground user terminal, clustering processing is performed on the plurality of ground user terminals to obtain a plurality of clustering clusters, and the number of the plurality of clustering clusters is the same as the number of base stations, so as to ensure that the current air base stations can better cover all ground user terminals, that is, improve the coverage integrity of the air-ground wireless network. And fully considering the impact of the sudden traffic on the network caused by the dynamic change of the user position in the disaster scenario and the situation of dynamic change of interference, the idea of clustering and clustering is adopted to cluster the ground user terminals, so as to reasonably deploy the positions of the air base stations, thereby improving the coverage integrity of the air-ground wireless network. In addition, based on the central position of the position area represented by each clustering cluster, the initial positions of each air base station are respectively determined, so as to ensure that the air base stations at the initial positions can better cover each ground user terminal, thereby improving the coverage integrity of the air-ground wireless network. And based on the initial positions of each air base station, an optimization problem is solved to obtain the deployment positions of each air base station, which can improve the solution efficiency of the optimization problem, that is, improve the deployment efficiency of the air-ground wireless network. And the objective function of the optimization problem is used to maximize the total rate of the ground user terminals. The total rate is the sum of the total data transmission rates of each ground user terminal. The total data transmission rate of any ground user terminal is the sum of the data transmission rates provided by each associated base station associated with the ground user terminal. Any associated base station is a base station associated with the ground user terminal in the air-ground wireless network, and the base station associated with the ground user terminal is used to provide services for the ground user terminal. Based on this, it is ensured that the throughput of the air-ground wireless network is maximized, thereby improving the capacity coverage of the air-ground wireless network, that is, improving the coverage integrity of the air-ground wireless network. Description of the Drawings

[0019] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0020] Figure 1 is one of the flow schematic diagrams of the method for deploying an air-ground wireless network provided by the present invention.

[0021] Figure 2 It is the second flow schematic diagram of the air-ground wireless network deployment method provided by the present invention.

[0022] Figure 3 It is the third flow schematic diagram of the air-ground wireless network deployment method provided by the present invention.

[0023] Figure 4 It is the structural schematic diagram of the air-ground wireless network deployment device provided by the present invention.

[0024] Figure 5 It is the structural schematic diagram of the electronic device provided by the present invention. Specific embodiments

[0025] To make the objectives, technical solutions and advantages of the present invention clearer, the technical solutions in the present invention will be clearly and completely described below with reference to the accompanying drawings in the present invention. Obviously, the described embodiments are some but not all of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments in the present invention without creative efforts shall fall within the protection scope of the present invention.

[0026] The present invention proposes the following embodiments. The following combines Figures 1-3 to describe the air-ground wireless network deployment method of the present invention.

[0027] Figure 1 It is the first flow schematic diagram of the air-ground wireless network deployment method provided by the present invention. As Figure 1 shown, the air-ground wireless network deployment method includes the following steps 110, step 120, step 130 and step 140.

[0028] Step 110, determine the number of base stations of the air base stations in the air-ground wireless network, and the positions of multiple ground user terminals to be covered by the air-ground wireless network.

[0029] Among them, the air-ground wireless network includes multiple air base stations and multiple ground base stations that can provide services.

[0030] In one embodiment, the air-ground wireless network is an integrated access and backhaul network, that is, the integrated access and backhaul technology is used to flexibly deploy the network. The integrated access and backhaul architecture means the close interworking between the access link and the backhaul link. Among them, the ground base stations use the same infrastructure and wireless channel resources to provide access and backhaul functions for ground user terminals and air base stations respectively.

[0031] Here, the number of base stations is the number of multiple air base stations, which is the number of air base stations that can provide communication services and can be deployed. In a specific embodiment, the number of base stations can be input by the user according to the actual situation.

[0032] Here, to avoid forming coverage holes, it is necessary to determine the positions of all ground user terminals that need to be covered by the air-ground wireless network. In a specific embodiment, the positions of multiple ground user terminals can be input by the user according to the actual situation.

[0033] Here, the ground base stations that can provide services are the base stations that can provide communication services, that is, the undamaged base stations. Further, if the ground base stations that can provide services cannot be determined, or if it is not certain which ground base stations can provide services, some ground base stations can be randomly removed from all the original ground base stations to simulate the disaster occurrence scenario.

[0034] Exemplarily, initially, the number of ground base stations is , after being affected by the disaster, some ground base stations are damaged, the damaged ground base stations are removed, and the remaining ground base stations are the base stations that can continue to provide services. The number of the remaining ground base stations is , the set of ground base stations that can provide services is . The set of aerial base stations is , the number of aerial base stations is . The set of base stations that can provide services in the air-ground wireless network is , where . The set of ground user terminals is , the number of ground user terminals is .

[0035] In one embodiment, initially, each aerial base station transmits signals with a preset fixed power. In one embodiment, initially, each aerial base station randomly hovers at the same height. In one embodiment, the satellite is used to establish the backhaul link for the aerial base stations.

[0036] Step 120, based on the number of base stations and the positions of the respective ground user terminals, perform clustering processing on the multiple ground user terminals to obtain multiple clustering clusters.

[0037] Among them, the number of the multiple clustering clusters is the same as the number of base stations.

[0038] Specifically, according to the positions of the respective ground user terminals, cluster the multiple ground user terminals so that the ground user terminals with close distances are grouped into one clustering cluster, and according to the number of aerial base stations, cluster the multiple ground user terminals so that the number of the multiple clustering clusters is the same as the number of base stations. Based on this, it is ensured that the current aerial base stations can better cover all ground user terminals.

[0039] In one embodiment, use the k-means clustering method to perform clustering processing on the multiple ground user terminals based on the number of base stations and the positions of the respective ground user terminals to obtain multiple clustering clusters.

[0040] Considering that in a disaster emergency scenario, due to the disaster affecting the normal movement of ground users (ground users carry ground user terminals), resulting in the phenomenon of ground user retention, the ground user terminals will exhibit an aggregation effect in the disaster area; that is, considering that the positions of ground users are initially evenly distributed, when a disaster occurs, there will be a certain aggregation in the disaster area; based on this, fully considering the impact of sudden traffic on the network caused by the dynamic change of user positions in the disaster scenario, as well as the situation of dynamic change of interference, the idea of clustering is adopted to cluster the ground user terminals, so as to reasonably deploy the positions of aerial base stations and ensure the coverage integrity of the air-ground wireless network.

[0041] Step 130, based on the central positions of the location areas represented by each of the clustering clusters, respectively determine the initial positions of each of the aerial base stations.

[0042] It should be noted that the above-mentioned clustering clusters are divided according to the positions of the ground user terminals. Based on this, the central positions of the location areas represented by each clustering cluster can be determined.

[0043] Specifically, for any clustering cluster and the aerial base station corresponding to this clustering cluster, the initial position of this aerial base station can directly be the central position of the location area represented by this clustering cluster, or the initial position of this aerial base station can be obtained by adjusting the central position of the location area represented by this clustering cluster.

[0044] It should be understood that based on the central positions of the location areas represented by each clustering cluster, respectively determine the initial positions of each aerial base station, so as to ensure that the aerial base stations at the initial positions can better cover each ground user terminal, thereby improving the coverage integrity of the air-ground wireless network, and subsequently solving the optimization problem based on the initial positions of each aerial base station can improve the solution efficiency of the optimization problem, that is, improve the deployment efficiency of the air-ground wireless network.

[0045] Step 140, based on the initial positions of each of the aerial base stations, solve the optimization problem to obtain the deployment positions of each of the aerial base stations.

[0046] Among them, the objective function of the optimization problem is used to maximize the total rate of the ground user terminals. The total rate is the sum of the total data transmission rates of each of the ground user terminals. The total data transmission rate of any one of the ground user terminals is the sum of the data transmission rates provided by each associated base station associated with the ground user terminal. Any one of the associated base stations is a base station associated with the ground user terminal in the air-ground wireless network, and the base station associated with the ground user terminal is used to provide services for the ground user terminal.

[0047] Here, the deployment location of the aerial base station is the optimal deployment location, and the total rate of the ground user terminals is relatively large at the optimal deployment location.

[0048] Exemplarily, the objective function of the optimization problem is as follows: ; In the formula, represents the set of ground user terminals, , and the number of ground user terminals is , represents the th ground user terminal, represents the th total data transmission rate of the ground user terminal, represents the total rate of the ground user terminals.

[0049] Among them, 's calculation formula is as follows: ; In the formula, represents the set of base stations that can provide services in the air-ground wireless network, , , represents the number of base stations of the aerial base station, represents the number of multiple ground base stations that can provide services, represents the th base station in the air-ground wireless network.

[0050] Among them, 's calculation formula is as follows: ; In the formula, represents the binary association variable (binary association indicator variable) between the ground user terminal and the base station , represents that the ground user terminal is associated with the base station , represents that the ground user terminal is not associated with the base station ; represents the data transmission rate (such as the instantaneous achievable rate) provided by the base station for the ground user terminal ; if , then represents the ground user terminal associated with the associated base station provided by for the ground user terminal Data transmission rate.

[0051] In some embodiments, the data transmission rate is calculated as follows: ; In the formula, represents the signal-to-noise ratio received by the ground user terminal from the base station at.

[0052] In one embodiment, the signal-to-noise ratio is calculated as follows: ; In the formula, represents the th air base station among multiple air base stations, represents the air base station 's transmission power; represents the ground user terminal and the air base station channel gain between; represents the set of air base stations, , represents the number of air base stations, represents the set in the th air base station; represents the air base station 's transmission power; represents the set of ground base stations that can provide services, , represents the number of multiple ground base stations that can provide services; represents the set in the th ground base station; represents the ground base station 's transmission power; represents the ground user terminal and the ground base station channel gain between; represents the noise power level; represents the set in the th ground base station, represents the ground base station 's transmission power; represents the ground user terminal and the ground base station channel gain between; represents the ground user terminal and the air base station Channel gain between them.

[0053] In a specific embodiment, based on the initial positions of each aerial base station, the optimization problem is first solved to obtain the user association variables and the transmission powers of each base station in the air-ground wireless network; the user association variables are used to characterize the association situation of each ground user terminal with each base station in the air-ground wireless network; based on the user association variables and the transmission powers of each base station in the air-ground wireless network, the optimization problem is solved to obtain the deployment positions of each aerial base station. Based on this, when it is necessary to solve the user association variables and the transmission powers of each base station in the air-ground wireless network, the optimization problem is first solved to obtain the user association variables and the transmission powers of each base station in the air-ground wireless network, and then the deployment positions of each aerial base station are solved, which can simplify the problem to be solved, thereby improving the solution efficiency of the optimization problem, that is, improving the deployment efficiency of the air-ground wireless network.

[0054] The air-ground wireless network deployment method provided by the embodiments of the present invention determines the number of base stations of the aerial base stations in the air-ground wireless network and the positions of multiple ground user terminals to be covered by the air-ground wireless network. Among them, the air-ground wireless network includes multiple aerial base stations and multiple ground base stations that can provide services. Based on the number of base stations and the positions of each ground user terminal, clustering processing is performed on the multiple ground user terminals to obtain multiple clustering clusters, and the number of the multiple clustering clusters is the same as the number of base stations, so as to ensure that the current aerial base stations can better cover all ground user terminals, that is, improve the coverage integrity of the air-ground wireless network. And fully consider the impact of the sudden traffic on the network caused by the dynamic change of the user position and the dynamic change of interference in the disaster scenario. The clustering idea is adopted to cluster the ground user terminals to reasonably deploy the positions of the aerial base stations, thereby improving the coverage integrity of the air-ground wireless network. In addition, based on the central positions of the position areas represented by each clustering cluster, the initial positions of each aerial base station are respectively determined, so as to ensure that the aerial base stations at the initial positions can better cover each ground user terminal, thereby improving the coverage integrity of the air-ground wireless network. And based on the initial positions of each aerial base station, the optimization problem is solved to obtain the deployment positions of each aerial base station, which can improve the solution efficiency of the optimization problem, that is, improve the deployment efficiency of the air-ground wireless network. And the objective function of the optimization problem is used to maximize the total rate of the ground user terminals. The total rate is the sum of the total data transmission rates of each ground user terminal. The total data transmission rate of any ground user terminal is the sum of the data transmission rates provided by each associated base station associated with the ground user terminal. Any associated base station is a base station in the air-ground wireless network associated with the ground user terminal, and the base station associated with the ground user terminal is used to provide services for the ground user terminal. Based on this, it is ensured that the throughput of the air-ground wireless network is maximized, thereby improving the capacity coverage of the air-ground wireless network, that is, improving the coverage integrity of the air-ground wireless network.

[0055] Based on any of the above embodiments, considering that the aerial base station uses a satellite for backhaul, but its backhaul capacity is limited, a ground base station that can provide services is used to provide a backhaul link for the aerial base station. That is, the backhaul capacity of the aerial base station using a satellite for backhaul is limited, and an undamaged ground base station is considered to provide backhaul for the aerial base station to enhance the coverage ability of the aerial base station.

[0056] It should be noted that the undamaged ground base station has a large-capacity optical fiber link, which can transmit information from the ground base station to the core network. That is, there is no congestion on the side of the undamaged ground base station. The in-band backhaul is used for the aerial base station. At the same time, the ground base station can also be used to supplement the backhaul link of the aerial base station. Therefore, a wireless backhaul link between the aerial base station and the ground base station is established.

[0057] Based on any of the above embodiments, Figure 2 is the second schematic flow chart of the air-ground wireless network deployment method provided by the present invention. As Figure 2 shown, the above step 140 includes step 141 and step 142.

[0058] Step 141, based on the initial positions of the aerial base stations, use convex optimization to solve the optimization problem to obtain the user association variables and the transmission powers of the base stations in the air-ground wireless network.

[0059] Among them, the user association variables are used to represent the association situations of the ground user terminals with the base stations in the air-ground wireless network respectively.

[0060] In the embodiments of the present invention, for the deployment of the air-ground wireless network, in addition to obtaining the deployment positions of the aerial base stations, it is also necessary to obtain the user association variables and the transmission powers of the base stations in the air-ground wireless network. Based on this, first solve the optimization problem to obtain the user association variables and the transmission powers of the base stations in the air-ground wireless network, and then solve the deployment positions of the aerial base stations, which can simplify the problem to be solved, thereby improving the solution efficiency of the optimization problem, that is, improving the deployment efficiency of the air-ground wireless network.

[0061] Since the optimization problem usually has a non-convex objective function with a non-linear constraint, and may have both integer variables and continuous variables, that is, the optimization problem may be a non-convex mixed integer NP-hard optimization problem. Based on this, first fix the positions of the aerial base stations, that is, the initial positions of the aerial base stations, and then use convex optimization to solve the optimization problem to obtain the user association variables and the transmission powers of the base stations in the air-ground wireless network, thereby improving the solution efficiency of the optimization problem, that is, improving the deployment efficiency of the air-ground wireless network.

[0062] Exemplarily, for the fixed positions of the aerial base stations (i.e., the initial positions of the aerial base stations), the optimization problem first solves the user association variables , the transmission power of the aerial base stations in the air-ground wireless network and the transmission power of the ground base stations in the air-ground wireless network , and the problem to be solved can be solved using convex optimization tools; after solving the optimization problem to obtain the user association variables and the transmission powers of the base stations in the air-ground wireless network, solve the optimization problem to obtain the deployment positions of the aerial base stations.

[0063] Step 142, based on the user association variables and the transmission powers of the base stations in the air-ground wireless network, solve the optimization problem to obtain the deployment positions of the aerial base stations.

[0064] In a specific embodiment, the particle swarm optimization algorithm is used to solve the optimization problem based on the user association variables and the transmission powers of the base stations in the air-ground wireless network to obtain the deployment positions of the aerial base stations, that is, to update the deployment positions of the aerial base stations. More specifically, the particle swarm optimization algorithm is used to determine the solution space of the optimization problem based on the user association variables and the transmission powers of the base stations in the air-ground wireless network, so as to update the positions of the aerial base stations using the particle swarm optimization algorithm in the solution space.

[0065] The air-ground wireless network deployment method provided by the embodiments of the present invention, through the above method, first solves the optimization problem to obtain the user association variables and the transmission powers of the base stations in the air-ground wireless network, and then solves the deployment positions of the aerial base stations, which can simplify the problem to be solved, thereby improving the solution efficiency of the optimization problem, that is, improving the deployment efficiency of the air-ground wireless network.

[0066] Based on any of the above embodiments, Figure 3 is the third flowchart of the air-ground wireless network deployment method provided by the present invention, as Figure 3 shown, the above step 142 includes steps 1421 to 1429.

[0067] Step 1421, based on the user association variables and the transmission powers of the base stations in the air-ground wireless network, determine the solution space of the optimization problem.

[0068] It should be noted that this optimization problem needs to solve for the user association variables, the transmission powers of the base stations in the air-ground wireless network, and the deployment positions of the aerial base stations. Based on this, the solution space of the optimization problem can be limited first based on the user association variables and the transmission powers of the base stations in the air-ground wireless network, so as to further solve the optimization problem in this solution space to obtain the deployment positions of the aerial base stations, that is, to update the deployment positions of the aerial base stations, thereby improving the solution efficiency of the optimization problem, that is, improving the deployment efficiency of the air-ground wireless network.

[0069] Step 1422: Randomly initialize the positions of all particles in the particle swarm in the solution space, and determine the initial annealing temperature based on the difference between the maximum fitness value and the minimum fitness value of the particle swarm.

[0070] Among them, the maximum fitness value is the maximum value among the fitness values of all particles in the particle swarm, and the minimum fitness value is the minimum value among the fitness values of all particles in the particle swarm.

[0071] Specifically, the difference between the maximum fitness value and the minimum fitness value can be directly determined as the initial annealing temperature, or further data processing can be performed on this difference to obtain the initial annealing temperature.

[0072] Exemplarily, the initial annealing temperature , represents the maximum fitness value of the initial particle swarm, represents the minimum fitness value of the initial particle swarm.

[0073] Step 1423: For each particle in the particle swarm, set the local optimal solution of the particle to the current position of the particle respectively, and determine the global optimal solution based on the local optimal solutions of all particles in the particle swarm.

[0074] Specifically, set the local optimal solution of the particle to its current position, and set the global optimal solution to the position of the best particle in the particle swarm.

[0075] Step 1424: If it is determined that the global optimal solution still needs to be updated, for any particle in the particle swarm, update the position and velocity of the particle. If the fitness value of the particle is better than the fitness value of the local optimal solution of the particle, update the local optimal solution of the particle to the current position of the particle. If the fitness value of the particle is better than the fitness value of the global optimal solution, update the global optimal solution to the current position of the particle.

[0076] Specifically, if the fitness value of the particle at the current position is better than the fitness value of the local optimal solution of the particle, update the local optimal solution of the particle to the current position of the particle. If the fitness value of the particle at the current position is better than the fitness value of the global optimal solution, update the global optimal solution to the current position of the particle.

[0077] In a specific embodiment, it is determined whether the algorithm convergence criterion is satisfied. If not, step 1424 is executed; otherwise, step 1429 is executed. Further, the algorithm convergence criterion may include, but is not limited to, the convergence condition of the fitness value, the convergence condition of the number of iterations, etc. For example, the convergence condition of the fitness value is that the difference between the fitness value of the globally optimal solution determined this time and the fitness value of the globally optimal solution determined last time is less than the preset fitness threshold; the convergence condition of the number of iterations is that the number of iterations reaches the maximum number of iterations. It may be determined that the globally optimal solution does not need to be updated only when multiple convergence conditions are satisfied, or it may be determined that the globally optimal solution does not need to be updated when one convergence condition is satisfied.

[0078] Step 1425, randomly generate a new position for the particle.

[0079] Specifically, a new position is randomly generated for the above particle to calculate the fitness difference between the old and new positions of the particle. This fitness difference is the difference between the fitness value of the particle at its current position and the fitness value of the particle at the new position.

[0080] Step 1426, if the fitness value of the particle at its current position is less than the fitness value of the particle at the new position, update the current position of the particle to the new position and reduce the annealing temperature.

[0081] Specifically, if the fitness difference between the old and new positions of the particle is less than 0, the particle enters the new position and a temperature reduction operation is performed.

[0082] In a specific embodiment, the annealing temperature is reduced by the following formula: ; In the formula, represents the annealing temperature.

[0083] Step 1427, if the fitness value of the particle at its current position is greater than or equal to the fitness value of the particle at the new position, and it is determined based on the annealing temperature to update the current position of the particle to the new position, reduce the annealing temperature, and return to the step where if the fitness value of the particle is better than the fitness value of the particle's local optimal solution, update the particle's local optimal solution to the particle's current position, and if the fitness value of the particle is better than the fitness value of the global optimal solution, update the global optimal solution to the particle's current position.

[0084] Specifically, if the fitness difference between the old and new positions of the particle is greater than or equal to 0, determine whether the particle enters the new position based on the annealing temperature. If it is determined that the particle enters the new position, the particle enters the new position and performs the temperature reduction operation, and then returns to execute step 1424 again. If the fitness value of the particle is better than the fitness value of the local optimal solution of the particle, update the local optimal solution of the particle to the current position of the particle. If the fitness value of the particle is better than the fitness value of the global optimal solution, update the global optimal solution to the current position of the particle; if it is determined that the particle does not enter the new position, perform the temperature reduction operation and determine whether the global optimal solution still needs to be updated.

[0085] Step 1428, if it is determined that the global optimal solution still needs to be updated, return to the step of updating the position and velocity of the particle.

[0086] In a specific embodiment, determine whether the algorithm convergence criterion is satisfied. If not, execute the step of updating the position and velocity of the particle, otherwise execute step 1429.

[0087] Specifically, use the iterative algorithm until convergence is reached, and then output the global optimal solution.

[0088] Step 1429, if it is determined that the global optimal solution does not need to be updated, obtain the deployment positions of the air base stations based on the global optimal solution.

[0089] Specifically, if it is determined that the global optimal solution does not need to be updated, output the global optimal solution to determine the deployment positions of the air base stations.

[0090] In the embodiment of the present invention, the idea of the simulated annealing strategy is introduced into the traditional particle swarm algorithm, and the standard particle swarm algorithm is improved by using the characteristic that simulated annealing can temporarily accept some inferior solutions with a certain probability. Finally, the iterative algorithm is used until convergence is reached. In other words, the particle swarm algorithm based on simulated annealing can increase the exploration ability of the solution space during the search process, help to jump out of the local optimal solution, and improve the global search ability of the algorithm. For example, first, randomly generate a certain number of particles, initialize their positions and velocities, and calculate the fitness value of each particle according to the fitness function defined by the problem; secondly, update the individual optimal position and the global optimal position. According to the fitness values of the individual historical optimal position and the current position, update the individual optimal position of each particle, and then update the global optimal position according to the individual optimal positions of all particles. Then, update the velocity and position of each particle; finally, introduce the simulated annealing strategy, accept solutions that are worse than the current solution with a certain probability, and repeat the iteration until the maximum number of iterations is reached or the accuracy requirement is met.

[0091] It should be understood that using the improved particle swarm algorithm described above to solve the deployment location of the aerial base station can further improve the deployment accuracy of the aerial base station, thereby enhancing the coverage integrity and capacity coverage of the air-ground wireless network. Compared with the existing particle swarm algorithm, the movement of its particles has no selectivity. Even if the fitness value of the next position of the particle is very poor, the particle still uses this position to replace the current position, which makes the particle easily jump out of a certain neighborhood near the optimal solution, and to a certain extent, the particle swarm algorithm performs poorly in local search ability. Based on this, the embodiment of the present invention combines the particle swarm algorithm with the simulated annealing algorithm, and utilizes the characteristic that the simulated annealing algorithm temporarily accepts some inferior solutions under the control of a certain probability, improves the local optimization ability of the existing particle swarm algorithm, and further improves the deployment accuracy of the aerial base station, thereby enhancing the coverage integrity and capacity coverage of the air-ground wireless network. In short, the particle swarm algorithm based on simulated annealing improves the global search ability compared with the traditional particle swarm algorithm.

[0092] The air-ground wireless network deployment method provided by the embodiment of the present invention, through the above method, utilizes the characteristic of temporarily accepting some inferior solutions under the control of a certain probability, improves the local optimization ability of the existing particle swarm algorithm, and further improves the deployment accuracy of the aerial base station, thereby enhancing the coverage integrity and capacity coverage of the air-ground wireless network.

[0093] Based on any of the above embodiments, in this method, the fitness value is determined based on the number of target ground user terminals and the number of target aerial base stations; the number of target ground user terminals is the number of ground user terminals among the multiple ground user terminals whose received signal-to-noise ratio of the access link is lower than the first target received signal-to-noise ratio; the number of target aerial base stations is the number of aerial base stations among the multiple aerial base stations whose received signal-to-noise ratio of the backhaul link is lower than the second target received signal-to-noise ratio.

[0094] Here, the first target received signal-to-noise ratio and the second target received signal-to-noise ratio can be set according to actual needs, and no specific limitation is made here.

[0095] Further, the first target received signal-to-noise ratio corresponding to different ground user terminals is different. Exemplarily, if among the multiple ground user terminals, the th ground user terminal in the received signal-to-noise ratio of the access link is lower than the th ground user terminal corresponding first target received signal-to-noise ratio , then this ground user terminal is counted as a target ground user terminal.

[0096] Further, the second target received signal-to-noise ratio corresponding to different aerial base stations is different. Exemplarily, if among the multiple aerial base stations, the An airborne base station The received signal-to-noise ratio of the backhaul link is lower than the th airborne base station corresponding second target received signal-to-noise ratio , then this airborne base station is counted as a target airborne base station.

[0097] Among them, the fitness value decreases as the number of target ground user terminals increases; the fitness value decreases as the number of target airborne base stations increases.

[0098] Exemplarily, the fitness value is determined based on a fitness function, and the fitness function is as follows: ; In the formula, represents the fitness value, represents the global optimal solution of the particle swarm, represents the objective function of the optimization problem, , both represent preset penalty parameters, represents the number of target ground user terminals, represents the number of target airborne base stations.

[0099] It should be understood that after a disaster, the ground base stations will be damaged, so the communication services provided by the ground base stations are limited. Therefore, it is crucial to achieve the efficient utilization of airborne base stations. An airborne base station should not only provide on-demand services for ground user terminals but also establish a reliable backhaul connection with undamaged ground base stations. This requires ensuring that the access link and the backhaul link of the airborne base station can match. Therefore, through the above method of determining the fitness value, it is ensured that the capacities of the access link and the backhaul link of the airborne base station match, so as to ensure that the airborne base station can quickly provide communication services for ground users in a disaster emergency scenario.

[0100] The method for deploying an air-ground wireless network provided by the embodiments of the present invention takes into account that the deployment of an airborne base station not only involves establishing a backhaul link with a ground base station but also involves establishing an access link with a ground user terminal. Therefore, the key to solving the deployment of an airborne base station is to select the backhaul link and the access link and make them match. Thus, through the above method of determining the fitness value, the deployment location of the airborne base station is determined, ensuring that the capacities of the access link and the backhaul link of the airborne base station match, so as to ensure that the airborne base station can quickly provide communication services for ground users in a disaster emergency scenario.

[0101] Based on any of the above embodiments, in this method, the above step 1427 includes: If the fitness value of the particle at its current position is greater than or equal to the fitness value of the particle at the new position, generate a random number within a preset value range; Based on the annealing temperature and the fitness difference between the fitness value of the particle at its current position and the fitness value of the particle at the new position, determine an update threshold; Determine that the random number is less than the update threshold, update the current position of the particle to the new position, reduce the annealing temperature, and return to the step of if the fitness value of the particle is better than the fitness value of the local optimal solution of the particle, update the local optimal solution of the particle to the current position of the particle, and if the fitness value of the particle is better than the fitness value of the global optimal solution, update the global optimal solution to the current position of the particle.

[0102] Exemplarily, the preset value range is from 0 to 1, that is, generate a random number r between (0, 1). If the random number , then the particle enters the new position and performs the temperature reduction operation, and then returns to execute again the step 1424 of if the fitness value of the particle is better than the fitness value of the local optimal solution of the particle, update the local optimal solution of the particle to the current position of the particle, and if the fitness value of the particle is better than the fitness value of the global optimal solution, update the global optimal solution to the current position of the particle; where represents the annealing temperature, represents the fitness difference, represents the update threshold.

[0103] The method for deploying an air-ground wireless network provided by the embodiments of the present invention, through the above manner, during the movement of the particle, when the next position of the particle is better than the current position, the particle moves to the next position; conversely, if the next position is worse than the current position, the particle does not directly move to the next position, but moves with a certain probability, and this probability is controlled by the annealing temperature; in this way, the particle will not blindly rush directly to the next position, but will act after probing with a certain probability; based on this, especially when the annealing temperature drops slowly enough, the particle will not easily jump out of the promising search area, thereby enhancing the local search ability of the particle, and further improving the deployment accuracy of the air base station, and thus enhancing the coverage integrity and capacity coverage of the air-ground wireless network.

[0104] Based on any of the above embodiments, after the above step 142, the method further includes: Based on the deployment positions of each of the air base stations, use a convex optimization method to solve the optimization problem to obtain the updated user association variables and the updated transmit powers of each base station in the air-ground wireless network.

[0105] It should be noted that initially, based on the initial positions of the aerial base stations, the convex optimization method is used to solve the optimization problem to obtain the user association variables and the transmission powers of the base stations in the air-ground wireless network. Since the deployment positions of the aerial base stations are variable, based on this, based on the updated deployment positions of the aerial base stations, the updated user association variables and the updated transmission powers of the base stations in the air-ground wireless network are re-solved.

[0106] In the air-ground wireless network deployment method provided by the embodiment of the present invention, after obtaining the optimal deployment positions of the aerial base stations, the convex optimization method is used again to solve the optimization problem to obtain the updated user association variables and the updated transmission powers of the base stations in the air-ground wireless network. Then, based on the updated user association variables, the updated transmission powers of the base stations in the air-ground wireless network, and the deployment positions of the aerial base stations, the air-ground wireless network is deployed, thereby improving the coverage integrity and capacity coverage of the air-ground wireless network.

[0107] Based on any of the above embodiments, in this method, the user association variables include a plurality of binary association variables, and any one of the binary association variables is used to represent the association situation between a ground user terminal and a base station in the air-ground wireless network.

[0108] Exemplarily, the user association variable , where represents the binary association variable (binary association indicator variable) of the ground user terminal and the base station , represents that the ground user terminal is associated with the base station , represents that the ground user terminal is not associated with the base station .

[0109] Correspondingly, step 141 above includes: Relax the binary association variables; Based on the initial positions of the aerial base stations, use the convex optimization method to solve the optimization problem to obtain the initial user association variables and the transmission powers of the base stations in the air-ground wireless network; Round each binary association variable in the initial user association variables to obtain the user association variables.

[0110] Since optimization problems usually involve non-convex objective functions with a non-linear constraint, and may have both integer variables and continuous variables, that is, the optimization problem may be a non-convex mixed-integer NP-hard optimization problem. Therefore, in order to alleviate the difficulty of the solved optimization problem, the binary association variables are first relaxed, which is the upper limit of performance, so as to simplify the solution problem, thereby improving the solution efficiency of the optimization problem, that is, improving the deployment efficiency of the air-ground wireless network.

[0111] Since the binary association variables are relaxed first, finally, each binary association variable in the initial user association variables needs to be rounded (0 or 1) to obtain the user association variables. The rounding method can be rounding or other methods.

[0112] The air-ground wireless network deployment method provided by the embodiments of the present invention first relaxes the binary association variables, and then rounds the solved initial user association variables, so as to simplify the solution problem, thereby improving the solution efficiency of the optimization problem, that is, improving the deployment efficiency of the air-ground wireless network.

[0113] Based on any of the above embodiments, in this method, the constraint conditions of the optimization problem include the first user association constraint condition; the first user association constraint condition is used to constrain that delay-sensitive ground user terminals can only be associated with ground base stations.

[0114] In other words, the first user association constraint condition is used to constrain that delay-sensitive ground user terminals can only be provided with communication services by ground base stations.

[0115] Considering that the backhaul link of the aerial base station will increase the delay, and in disaster scenarios, for example, the ground users of the rescue team need to use delay-sensitive applications to provide timely rescue for the affected area as soon as possible. Therefore, delay-sensitive ground user terminals can only be associated with ground base stations.

[0116] Exemplarily, the first user association constraint condition is as follows: ; In the formula, represents the set of aerial base stations, , represents the number of base stations of the aerial base station, represents the th aerial base station in the set ; represents the set of ground user terminals, , the number of ground user terminals is , represents the th ground user terminal in the set ; represents the ground user terminal and the aerial base station binary association variable (binary association indicator variable), indicating that the ground user terminal is associated with the aerial base station is associated, indicating that the ground user terminal is not associated with the aerial base station is not associated; , indicating that the ground user terminal is delay-sensitive, indicating that the ground user terminal is not delay-sensitive.

[0117] Based on any of the above embodiments, in this method, the constraint conditions of the optimization problem further include at least one of the following: signal-to-noise ratio constraint condition, second user association constraint condition, access rate constraint condition, base station transmission power constraint condition, and aerial base station location constraint condition.

[0118] Among them, the signal-to-noise ratio constraint condition is used to ensure that the received signal-to-noise ratio of each ground user terminal is not less than a preset received signal-to-noise ratio threshold (such as a predefined minimum received signal-to-noise ratio).

[0119] Exemplarily, the signal-to-noise ratio constraint condition is as follows: ; In the formula, represents the set of ground user terminals, , the number of ground user terminals is , represents the set the th ground user terminal in, represents the th received signal-to-noise ratio of the ground user terminal, represents the preset received signal-to-noise ratio threshold.

[0120] Based on this signal-to-noise ratio constraint condition, the QoS (Quality of Service) of the ground user terminal can be guaranteed, thereby improving the coverage integrity and capacity coverage of the air-ground wireless network.

[0121] Among them, the second user association constraint condition is used to ensure that a ground user terminal can only be associated with one base station.

[0122] Exemplarily, the second user association constraint condition is as follows: ; In the formula, represents the set of ground user terminals, , the number of ground user terminals is , represents the set in the -th ground user terminal, represents the set of base stations that can provide services in the air-ground wireless network, represents the -th base station in the air-ground wireless network, represents the ground user terminal and the base station 's binary association variable (binary association indicator variable), represents the ground user terminal and the base station are associated, represents the ground user terminal and the base station are not associated.

[0123] Based on this second user association constraint condition, it can be ensured that each ground user terminal can only be served by one air base station or ground base station, thereby improving the coverage integrity and capacity coverage of the air-ground wireless network.

[0124] Among them, the access rate constraint condition is used to ensure that the access rate provided by each air base station to the ground user terminal is not higher than the backhaul rate of the air base station; the access rate provided by any air base station to the ground user terminal is the sum of the data rates received by each ground user terminal from the air base station, and the backhaul rate of the air base station is determined based on the backhaul capacity provided by the satellite to the air base station and the backhaul capacity provided by the ground base station associated with the air base station.

[0125] Among them, the backhaul capacity provided by the satellite to the air base station is usually fixed.

[0126] Exemplarily, the access rate constraint condition is as follows: ; In the formula, represents the set of ground user terminals, , the number of ground user terminals is , represents the set in the -th ground user terminal; represents the set of air base stations, represents the set in the -th air base station; represents the ground user terminal receiving data from the air base station Received data rate; Indicates the backhaul capacity provided by the ground base station associated with the air base station to the air base station ; Indicates the backhaul capacity provided by the satellite to the air base station ;

[0127] In one embodiment, the backhaul capacity is calculated based on the following formula: ; Wherein, Indicates the signal-to-noise ratio received by the air base station from the associated ground base station ;

[0128] In one embodiment, the signal-to-noise ratio is calculated based on the following formula: ; Wherein, Indicates the transmit power of the ground base station ; Indicates the transmit power of the ground base station and the air base station channel gain between; Indicates the noise power level.

[0129] Based on the access rate constraint condition, it can be ensured that the backhaul capacity supported by the air base station should not exceed its backhaul capacity. That is, in the post-disaster emergency scenario, deploying an integrated space-air-ground network and using the integrated access and backhaul technology, fully considering the wireless backhaul and limited backhaul capacity of the air base station, improving the reliability of link reconstruction between the air base station and the available ground base stations and ground user terminals, so as to improve the coverage integrity and capacity coverage of the air-ground wireless network.

[0130] Among them, the base station transmit power constraint condition is used to constrain the transmit power of each base station in the air-ground wireless network not to exceed its maximum transmit power.

[0131] Exemplarily, the base station transmit power constraint condition is as follows: ; ; Wherein, Indicates the transmit power of the ground base station ; Indicates the maximum transmit power of the ground base station; Indicates the transmit power of the air base station ; Represents the maximum transmission power of the aerial base station.

[0132] Among them, the aerial base station location constraint condition is used to constrain the deployment area of each aerial base station.

[0133] Exemplarily, the aerial base station location constraint condition is as follows: ; In the formula, represents the set of aerial base stations, represents the set in the th aerial base station, represents the deployment location of the aerial base station , represents the flight area where the aerial base station can fly (i.e., the deployment area where the aerial base station can be deployed).

[0134] The air-ground wireless network deployment method provided by the embodiments of the present invention solves the optimization problem through the above constraint conditions, so as to ensure the signal coverage and capacity coverage of the air-ground wireless network, thereby improving the coverage integrity and capacity coverage of the air-ground wireless network.

[0135] Based on any of the above embodiments, the aerial base station uses NOMA (Non-Orthogonal Multiple Access), and the ground user terminal adopts SIC (Successive Interference Cancellation) technology, so as to reduce the mutual interference of all ground user terminals associated with the aerial base station. Randomly group all ground user terminals associated with the aerial base station. The ground user terminals in the same group share the same time-frequency resources using NOMA technology, and orthogonality is maintained between groups, that is, inter-group interference is ignored. Then, number each ground user terminal group in ascending order according to the channel strength. By applying SIC, the signals of other ground user terminals can be decoded and subtracted. The downlink access power and backhaul power allocation are also initialized with equal power allocation based on the number of ground user terminals associated with each base station.

[0136] To facilitate the understanding of the above embodiments, a specific embodiment is described here. The process of solving the user association variable, the transmission power of each base station in the air-ground wireless network, and the deployment location of each aerial base station in the air-ground wireless network is as follows: The first step is to input the locations of multiple ground user terminals, the locations of multiple available ground base stations, and the number of base stations of the aerial base station; In the second step, based on the number of base stations and the locations of each terrestrial user terminal, perform clustering processing on multiple terrestrial user terminals to obtain multiple clustering clusters; based on the central locations of the location areas represented by each clustering cluster, respectively determine the initial locations of each aerial base station; establish a backhaul connection between the aerial base station and the terrestrial base stations that can provide services; set the iteration number t = 1; In the third step, calculate the channel gain and signal-to-noise ratio between each base station and the associated terrestrial user terminal in the air-ground wireless network; In the fourth step, execute the following iterative process: (1) When the iteration number t is less than the maximum iteration number and the convergence condition of the objective function of the convex optimization method is not satisfied, based on the locations of each aerial base station (its initial location when t = 1), use the convex optimization method to solve the optimization problem to obtain the user association variables and the transmission power of each base station in the air-ground wireless network; (2) When the convergence condition of the fitness value is not satisfied, randomly initialize the locations of each particle in the particle swarm in the solution space, and based on the difference between the maximum fitness value and the minimum fitness value of the particle swarm, determine the initial annealing temperature; (3) For each particle in the particle swarm, respectively set the local optimal solution of the particle as the current location of the particle, and based on the local optimal solutions of each particle in the particle swarm, determine the global optimal solution; (4) Determine whether the convergence condition of the fitness value is satisfied. If it is satisfied, execute (13); if not, execute (5); (5) Update the location and velocity of the particle; (6) If the fitness value of the particle is better than the fitness value of the local optimal solution of the particle, update the local optimal solution of the particle to the current location of the particle. If the fitness value of the particle is better than the fitness value of the global optimal solution of the particle, update the global optimal solution to the current location of the particle; (7) Randomly generate a new location of the particle; (8) If the fitness value of the particle at its current location is less than the fitness value of the particle at the new location, update the current location of the particle to the new location and execute (10); (9) If the fitness value of the particle at its current location is greater than or equal to the fitness value of the particle at the new location, and based on the annealing temperature, it is determined to update the current location of the particle to the new location, execute (10) and return to (6); (10) Reduce the annealing temperature; (11) t = t + 1; (12) Determine whether the algorithm convergence criterion is satisfied. If it is satisfied, execute (13); if not, turn to (5); (13) Output the global optimal solution, and the algorithm ends. That is, output the user association variables, the transmission power of each base station, and the deployment locations of each aerial base station to complete the on-demand deployment of the network in the post-disaster emergency scenario.

[0137] When calculating the channel gain between two ends, the following embodiments can be referred to.

[0138] The air-to-ground path loss depends on the height of the aerial base station and the elevation angle between the aerial base station and the ground user terminal. It mainly has two propagation groups, corresponding to the receiver (ground user terminal) with line-of-sight (LoS) connection and the transmitter (aerial base station) with non-line-of-sight (NLoS) connection respectively. Due to strong reflection and diffraction, the ground user terminal can still receive signals from the transmitter.

[0139] Exemplarily, the total power reduction of the signal transmitted from the aerial base station to the ground user terminal can be calculated using the following formula: ; In the formula, represents the total path loss, represents the free space path loss, represents the line-of-sight path loss or non-line-of-sight path loss (i.e., the excessive path loss caused by the LoS channel or NLoS channel between the aerial base station and the ground user terminal).

[0140] Among them, can be represented by a Gaussian distribution, , is a constant value, only depends on the average excessive path loss shown by the environment, , represents the -th transmission power of the aerial base station, represents the attenuation constant related to the environment, , and are respectively the height of the aerial base station and the distance projection of the ground user terminal on the ground.

[0141] Among them, for the backhaul link, the calculation formula of the free space path loss FSPL is as follows: ; In the formula, is the carrier frequency, represents the speed of light, represents the distance between the transmitter and the receiver.

[0142] Among them, the probability of having a LoS connection between the aerial base station and the ground user terminal can be formulated as: , wherein, and are constant values depending on the environment, , and are respectively the height of the aerial base station and the distance projection of the ground user terminal on the ground.

[0143] Among them, the antenna gain is approximately: ; wherein, , represents the half-power beamwidth of the directional antenna of the aerial base station, , is negligible.

[0144] For example, the average path loss in dB (decibels) can be expressed as . Among them is the distance between the transmitter and the receiver, in kilometers.

[0145] Based on the above embodiments, the present invention proposes a method for on-demand deployment of an access and backhaul integrated network for disaster emergency scenarios, so as to provide communication services for ground user terminals in a timely manner through aerial base stations, so as to achieve signal coverage and capacity coverage of the disaster emergency network. Specifically, using access and backhaul integrated technology, and taking ground user association, base station transmit power (downlink power) allocation, and the deployment location of aerial base stations as optimization objectives, on-demand coverage of ground user terminals in disaster scenarios is achieved. More specifically, a joint optimization method of network deployment and resource allocation that maximizes capacity coverage is adopted to solve the problems of the association strategy between ground user terminals and base stations, the reasonable allocation of the downlink power of base stations, and the location deployment of aerial base stations in the air-ground-space integrated wireless network assisted by aerial base stations in disaster emergency scenarios, achieving the effects of on-demand coverage of the disaster area and maximizing system throughput.

[0146] Among them, the aerial base station can supplement or assist the ground base station, and has advantages such as low deployment cost and on-demand dynamic deployment.

[0147] Next, the air-ground wireless network deployment device provided by the present invention will be described. The air-ground wireless network deployment device described below can be correspondingly referred to the air-ground wireless network deployment method described above.

[0148] Figure 4 is a schematic structural diagram of the air-ground wireless network deployment device provided by the present invention, as shown in Figure 4As shown, the device for deploying an air-ground wireless network includes a number determination module, a user clustering module, a location determination module, and a location solution module.

[0149] The number determination module 410 is configured to determine the number of air base stations in the air-ground wireless network and the locations of a plurality of ground user terminals to be covered by the air-ground wireless network; the air-ground wireless network includes a plurality of air base stations and a plurality of ground base stations that can provide services.

[0150] The user clustering module 420 is configured to perform clustering processing on the plurality of ground user terminals based on the number of base stations and the locations of the ground user terminals to obtain a plurality of clustering clusters; the number of the plurality of clustering clusters is the same as the number of base stations.

[0151] The location determination module 430 is configured to respectively determine the initial locations of the air base stations based on the central locations of the location regions represented by the clustering clusters.

[0152] The location solution module 440 is configured to solve an optimization problem based on the initial locations of the air base stations to obtain the deployment locations of the air base stations; the objective function of the optimization problem is used to maximize the total rate of the ground user terminals, the total rate is the sum of the total data transmission rates of the ground user terminals, the total data transmission rate of any one of the ground user terminals is the sum of the data transmission rates provided by the associated base stations associated with the ground user terminal, any one of the associated base stations is a base station in the air-ground wireless network associated with the ground user terminal, and the base station associated with the ground user terminal is used to provide services for the ground user terminal.

[0153] Figure 5 Illustrated is a schematic diagram of the physical structure of an electronic device, such as Figure 5As shown in the figure, the electronic device may include: a processor 510, a communications interface 520, a memory 530, and a communication bus 540. Among them, the processor 510, the communications interface 520, and the memory 530 complete communication with each other through the communication bus 540. The processor 510 may call the logical instructions in the memory 530 to execute the method for deploying an air-ground wireless network. The method includes: determining the number of base stations of the air base stations in the air-ground wireless network and the positions of a plurality of ground user terminals to be covered by the air-ground wireless network; the air-ground wireless network includes a plurality of air base stations and a plurality of ground base stations that can provide services; based on the number of base stations and the positions of the ground user terminals, clustering processing is performed on the plurality of ground user terminals to obtain a plurality of clustering clusters; the number of the plurality of clustering clusters is the same as the number of base stations; based on the central positions of the position regions represented by the clustering clusters, the initial positions of the air base stations are respectively determined; based on the initial positions of the air base stations, an optimization problem is solved to obtain the deployment positions of the air base stations; the objective function of the optimization problem is used to maximize the total rate of the ground user terminals, the total rate is the sum of the total data transmission rates of the ground user terminals, and the total data transmission rate of any one of the ground user terminals is the sum of the data transmission rates provided by the associated base stations associated with the ground user terminal, and any one of the associated base stations is a base station associated with the ground user terminal in the air-ground wireless network, and the base station associated with the ground user terminal is used to provide services for the ground user terminal.

[0154] In addition, when the logical instructions in the above-mentioned memory 530 are implemented in the form of software functional units and sold or used as an independent product, they may be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or a part of this technical solution, may be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of the present invention. The foregoing storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memories (ROM, Read-Only Memory), random access memories (RAM, Random Access Memory), magnetic disks, or optical discs that can store program codes.

[0155] On the other hand, the present invention also provides a computer program product, which includes a computer program. The computer program can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the air-ground wireless network deployment method provided by each of the above methods. The method includes: determining the number of base stations of the air base stations in the air-ground wireless network, and the positions of a plurality of ground user terminals to be covered by the air-ground wireless network; the air-ground wireless network includes a plurality of air base stations and a plurality of ground base stations that can provide services; based on the number of base stations and the positions of each of the ground user terminals, performing clustering processing on the plurality of ground user terminals to obtain a plurality of clustering clusters; the number of the plurality of clustering clusters is the same as the number of base stations; based on the central positions of the position areas represented by each of the clustering clusters, respectively determining the initial positions of each of the air base stations; based on the initial positions of each of the air base stations, solving an optimization problem to obtain the deployment positions of each of the air base stations; the objective function of the optimization problem is used to maximize the total rate of the ground user terminals, the total rate is the sum of the total data transmission rates of each of the ground user terminals, the total data transmission rate of any one of the ground user terminals is the sum of the data transmission rates of the ground user terminals provided by each associated base station associated with the ground user terminal, any one of the associated base stations is a base station in the air-ground wireless network associated with the ground user terminal, and the base station associated with the ground user terminal is used to provide services for the ground user terminal.

[0156] In another aspect, the present invention also provides a non-transitory computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, it implements the air-ground wireless network deployment method provided by the above-mentioned various methods. The method includes: determining the number of base stations of the air-ground wireless network and the positions of a plurality of ground user terminals to be covered by the air-ground wireless network; the air-ground wireless network includes a plurality of air base stations and a plurality of ground base stations that can provide services; based on the number of base stations and the positions of the ground user terminals, clustering the plurality of ground user terminals to obtain a plurality of clustering clusters; the number of the plurality of clustering clusters is the same as the number of base stations; based on the central positions of the position regions represented by the clustering clusters, respectively determining the initial positions of the air base stations; based on the initial positions of the air base stations, solving an optimization problem to obtain the deployment positions of the air base stations; the objective function of the optimization problem is used to maximize the total rate of the ground user terminals, the total rate is the sum of the total data transmission rates of the ground user terminals, the total data transmission rate of any ground user terminal is the sum of the data transmission rates provided by the associated base stations associated with the ground user terminal, any associated base station is a base station associated with the ground user terminal in the air-ground wireless network, and the base station associated with the ground user terminal is used to provide services for the ground user terminal.

[0157] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art can understand and implement it without creative labor.

[0158] Through the description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on such an understanding, the essence of the above technical solution or the part that contributes to the prior art can be embodied in the form of a software product. The computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0159] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A method for deploying an air-ground wireless network, characterized in that, Including: Determine the number of aerial base stations in the air-ground wireless network, and the locations of multiple ground user terminals to be covered by the air-ground wireless network; The air-ground wireless network includes multiple aerial base stations and multiple available ground base stations; Based on the number of base stations and the locations of the ground user terminals, perform clustering processing on the multiple ground user terminals to obtain multiple clustering clusters; the number of the multiple clustering clusters is the same as the number of base stations; Based on the central positions of the location areas represented by the clustering clusters, respectively determine the initial positions of the aerial base stations; Based on the initial positions of the aerial base stations, solve the optimization problem to obtain the deployment positions of the aerial base stations; the objective function of the optimization problem is used to maximize the total rate of the ground user terminals, the total rate is the sum of the total data transmission rates of the ground user terminals, and the total data transmission rate of any ground user terminal is the sum of the data transmission rates provided by the associated base stations associated with the ground user terminal, and any associated base station is a base station associated with the ground user terminal in the air-ground wireless network, and the base station associated with the ground user terminal is used to provide services for the ground user terminal.

2. The method for deploying an airspace wireless network according to claim 1, wherein The step of based on the initial positions of the aerial base stations, solving the optimization problem to obtain the deployment positions of the aerial base stations includes: Based on the initial positions of the aerial base stations, use convex optimization to solve the optimization problem to obtain the user association variables and the transmission powers of the base stations in the air-ground wireless network; the user association variables are used to represent the association situations of the ground user terminals with the base stations in the air-ground wireless network respectively; Based on the user association variables and the transmission powers of the base stations in the air-ground wireless network, solve the optimization problem to obtain the deployment positions of the aerial base stations.

3. The method for deploying an airspace wireless network according to claim 2, wherein The step of based on the user association variables and the transmission powers of the base stations in the air-ground wireless network, solving the optimization problem to obtain the deployment positions of the aerial base stations includes: Based on the user association variables and the transmission powers of the base stations in the air-ground wireless network, determine the solution space of the optimization problem; Randomly initialize the positions of the particles in the particle swarm in the solution space, and determine the initial annealing temperature based on the difference between the maximum fitness value and the minimum fitness value of the particle swarm; the maximum fitness value is the maximum value among the fitness values of the particles in the particle swarm, and the minimum fitness value is the minimum value among the fitness values of the particles in the particle swarm; For each particle in the particle swarm, respectively set the local optimal solution of the particle to the current position of the particle, and determine the global optimal solution based on the local optimal solutions of the particles in the particle swarm; If it is determined that the global optimal solution still needs to be updated, for any particle in the particle swarm, update the position and velocity of the particle. If the fitness value of the particle is better than the fitness value of the local optimal solution of the particle, update the local optimal solution of the particle to the current position of the particle. If the fitness value of the particle is better than the fitness value of the global optimal solution, update the global optimal solution to the current position of the particle; Randomly generate a new position for the particle; If the fitness value of the particle at its current position is less than the fitness value of the particle at the new position, update the current position of the particle to the new position and decrease the annealing temperature; If the fitness value of the particle at its current position is greater than or equal to the fitness value of the particle at the new position, and it is determined to update the current position of the particle to the new position based on the annealing temperature, decrease the annealing temperature, and return to the step of if the fitness value of the particle is better than the fitness value of the local optimal solution of the particle, update the local optimal solution of the particle to the current position of the particle. If the fitness value of the particle is better than the fitness value of the global optimal solution, update the global optimal solution to the current position of the particle; If it is determined that the global optimal solution still needs to be updated, return to the step of updating the position and velocity of the particle; If it is determined that the global optimal solution does not need to be updated, obtain the deployment positions of the air base stations based on the global optimal solution.

4. The method for deploying an airspace wireless network according to claim 3, wherein The fitness value is determined based on the target number of ground user terminals and the target number of air base stations; The target number of ground user terminals is the number of ground user terminals among the multiple ground user terminals whose received signal-to-noise ratio of the access link is lower than the first target received signal-to-noise ratio; The target number of air base stations is the number of air base stations among the multiple air base stations whose received signal-to-noise ratio of the backhaul link is lower than the second target received signal-to-noise ratio.

5. The method for deploying an airspace wireless network according to claim 3, characterized in that The step of if the fitness value of the particle at its current position is greater than or equal to the fitness value of the particle at the new position, and it is determined to update the current position of the particle to the new position based on the annealing temperature, decrease the annealing temperature, and return to the step of if the fitness value of the particle is better than the fitness value of the local optimal solution of the particle, update the local optimal solution of the particle to the current position of the particle. If the fitness value of the particle is better than the fitness value of the global optimal solution, update the global optimal solution to the current position of the particle includes: If the fitness value of the particle at its current position is greater than or equal to the fitness value of the particle at the new position, generate a random number within a preset value range; Based on the annealing temperature and the fitness difference between the fitness value of the particle at its current position and the fitness value of the particle at the new position, determine an update threshold; Determine that the random number is less than the update threshold, update the current position of the particle to the new position, decrease the annealing temperature, and return the step of updating the local optimal solution of the particle to the current position of the particle if the fitness value of the particle is better than the fitness value of the local optimal solution of the particle, and updating the global optimal solution to the current position of the particle if the fitness value of the particle is better than the fitness value of the global optimal solution.

6. The method for deploying an airspace wireless network according to claim 2, wherein After solving the optimization problem based on the user association variable and the transmission powers of the base stations in the air-ground wireless network to obtain the deployment positions of the air base stations, the method further includes: Based on the deployment positions of the air base stations, using convex optimization to solve the optimization problem to obtain the updated user association variable and the updated transmission powers of the base stations in the air-ground wireless network.

7. The method for deploying an airspace wireless network according to claim 2, wherein The user association variable includes a plurality of binary association variables, and any one of the binary association variables is used to represent the association situation between a ground user terminal and a base station in the air-ground wireless network; The method of solving the optimization problem based on the initial positions of the air base stations by using convex optimization to obtain the user association variable and the transmission powers of the base stations in the air-ground wireless network includes: Relax the binary association variables; Based on the initial positions of the air base stations, use convex optimization to solve the optimization problem to obtain the initial user association variable and the transmission powers of the base stations in the air-ground wireless network; Round each binary association variable in the initial user association variable to obtain the user association variable.

8. The method for deploying an airspace wireless network according to any one of claims 1 to 7, characterized in that The constraint conditions of the optimization problem include the first user association constraint condition; The first user association constraint condition is used to constrain that delay-sensitive ground user terminals can only be associated with ground base stations.

9. The method for deploying an airspace wireless network according to claim 8, wherein The constraint conditions further include the signal-to-noise ratio constraint condition, the second user association constraint condition, the access rate constraint condition, the base station transmission power constraint condition, and the air base station position constraint condition; The signal-to-noise ratio constraint condition is used to constrain that the received signal-to-noise ratios of the ground user terminals are not less than a preset received signal-to-noise ratio threshold; The second user association constraint condition is used to constrain that a ground user terminal can only be associated with one base station; The access rate constraint condition is used to constrain that the access rates provided by the air base stations for the ground user terminals are not higher than the backhaul rates of the air base stations; the access rate provided by any air base station for the ground user terminals is the sum of the data rates received by the ground user terminals from the air base station, and the backhaul rate of the air base station is determined based on the backhaul capacity provided by the satellite to the air base station and the backhaul capacity provided by the ground base station associated with the air base station; The base station transmission power constraint condition is used to constrain that the transmission powers of the base stations in the air-ground wireless network do not exceed their maximum transmission powers; The air base station position constraint condition is used to constrain the deployment areas of the air base stations.

10. An air-ground wireless network deployment device, characterized in that, Including: A number determination module, configured to determine the number of base stations of the air base stations in the air-ground wireless network, and the positions of a plurality of ground user terminals to be covered by the air-ground wireless network; The described air-ground wireless network includes a plurality of aerial base stations and a plurality of service-providing ground base stations; A user clustering module, configured to perform clustering processing on the plurality of ground user terminals based on the number of the base stations and the positions of the respective ground user terminals, to obtain a plurality of clustering clusters; the number of the plurality of clustering clusters is the same as the number of the base stations; A position determination module, configured to respectively determine the initial positions of the respective aerial base stations based on the central positions of the position regions represented by the respective clustering clusters; A position solution module, configured to solve an optimization problem based on the initial positions of the respective aerial base stations to obtain the deployment positions of the respective aerial base stations; the objective function of the optimization problem is used to maximize the total rate of the ground user terminals, the total rate is the sum of the total data transmission rates of the respective ground user terminals, the total data transmission rate of any one of the ground user terminals is the sum of the data transmission rates provided by the respective associated base stations associated with the ground user terminal, any one of the associated base stations is a base station in the air-ground wireless network associated with the ground user terminal, and the base station associated with the ground user terminal is used to provide services for the ground user terminal.

11. An electronic device, comprising a memory, a processor, and a computer program stored on the memory and running on the processor, wherein, When the processor executes the computer program, it implements the air-ground wireless network deployment method according to any one of claims 1 to 9.

12. A non-transitory computer-readable storage medium storing a computer program thereon, characterized in that, When the computer program is executed by a processor, it implements the air-ground wireless network deployment method according to any one of claims 1 to 9.

13. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the air-ground wireless network deployment method according to any one of claims 1 to 9.

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