CN110996328B - Unmanned aerial vehicle base station deployment position determining method and device and electronic equipment - Google Patents

Unmanned aerial vehicle base station deployment position determining method and device and electronic equipment Download PDF

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CN110996328B
CN110996328B CN201911164535.1A CN201911164535A CN110996328B CN 110996328 B CN110996328 B CN 110996328B CN 201911164535 A CN201911164535 A CN 201911164535A CN 110996328 B CN110996328 B CN 110996328B
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CN110996328A (en
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赵东
马华东
张静
张献忠
孙壬辛
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Beijing University of Posts and Telecommunications
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W16/00—Network planning, e.g. coverage or traffic planning tools; Network deployment, e.g. resource partitioning or cells structures
    • H04W16/18—Network planning tools
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/14—Relay systems
    • H04B7/15—Active relay systems
    • H04B7/185—Space-based or airborne stations; Stations for satellite systems
    • H04B7/18502—Airborne stations
    • H04B7/18504—Aircraft used as relay or high altitude atmospheric platform
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W16/00—Network planning, e.g. coverage or traffic planning tools; Network deployment, e.g. resource partitioning or cells structures
    • H04W16/22—Traffic simulation tools or models
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W24/00—Supervisory, monitoring or testing arrangements
    • H04W24/06—Testing, supervising or monitoring using simulated traffic
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W24/00—Supervisory, monitoring or testing arrangements
    • H04W24/08—Testing, supervising or monitoring using real traffic
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W64/00—Locating users or terminals or network equipment for network management purposes, e.g. mobility management
    • H04W64/003—Locating users or terminals or network equipment for network management purposes, e.g. mobility management locating network equipment
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W64/00—Locating users or terminals or network equipment for network management purposes, e.g. mobility management
    • H04W64/006—Locating users or terminals or network equipment for network management purposes, e.g. mobility management with additional information processing, e.g. for direction or speed determination

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Abstract

The embodiment of the invention provides a method and a device for determining the deployment position of an unmanned aerial vehicle base station and electronic equipment, wherein the method comprises the following steps: the method comprises the steps of simulating the average simulated network throughput of each simulated user terminal in a to-be-deployed area aiming at each sub-area, selecting a first preset number of sub-areas from the sub-areas to serve as target sub-areas, obtaining the real network throughput of each real user terminal aiming at each preset deployment position in the target sub-areas, calculating the sum value of the real network throughput of each real user terminal aiming at the preset deployment positions, and selecting a second preset number of preset deployment positions from the preset deployment positions in the target sub-areas to serve as the deployment positions of the unmanned aerial vehicle base station. By adopting the scheme provided by the embodiment of the invention, the network throughput of each user in the target area is improved.

Description

Unmanned aerial vehicle base station deployment position determining method and device and electronic equipment
Technical Field
The invention relates to the technical field of wireless communication, in particular to a method and a device for determining the deployment position of an unmanned aerial vehicle base station, electronic equipment and a storage medium.
Background
In recent years, there have been many researches on mobile base stations, such as a wireless fidelity (WiFi) and a drone mobile base station, which can provide network services in various scenarios. The network service provided by using the unmanned aerial vehicle as the mobile base station has many advantages: the unmanned aerial vehicle has high degree of freedom, the unmanned aerial vehicle is used as a mobile base station to overcome the limitation of geographic environment, and the cooperative service of the unmanned aerial vehicle base stations can adjust the network capacity distribution according to the network requirements of users.
Current drone base station deployments are primarily targeted at maximizing the number of coverage users. However, a drone base station deployment that simply targets maximizing the number of users covered may result in poor network quality for the users. For example, when the network throughput demand of the user covered by the drone base station exceeds the upper limit of the network throughput that the drone base station can provide, the network quality provided by the drone base station is poor, and the user experience is poor.
Disclosure of Invention
The embodiment of the invention aims to provide a method and a device for determining the deployment position of an unmanned aerial vehicle base station and electronic equipment, so as to improve the network throughput of each user in a target area and improve the network quality of the user.
In order to achieve the above object, an embodiment of the present invention provides a method for determining a deployment position of an unmanned aerial vehicle base station, where a to-be-deployed area is divided into a plurality of sub-areas, and the to-be-deployed area includes a plurality of preset deployment positions, where the method includes:
simulating the average simulated network throughput of each simulated user terminal aiming at each sub-area in the area to be deployed based on a network throughput simulation model;
according to the sequence that the sum of the average simulated network throughputs of the sub-areas is from large to small, selecting a first preset number of sub-areas from the sub-areas as a target sub-area, wherein the sum of the average simulated network throughputs of the sub-areas is the sum of the average simulated network throughputs of each simulated user terminal in the area to be deployed for the sub-area;
acquiring the real network throughput of each real user terminal in the to-be-deployed area aiming at each preset deployment position in the target sub-area;
calculating the sum of the real network throughput of each real user terminal in the to-be-deployed area aiming at each preset deployment position in the target sub-area, wherein the sum is used as the sum of the real network throughput of the preset deployment position;
and selecting a second preset number of preset deployment positions from the preset deployment positions in the target sub-area as the deployment positions of the unmanned aerial vehicle base station according to the sequence from large to small of the sum of the real network throughputs of all the preset deployment positions in the target sub-area.
Further, the simulating the average simulated network throughput of each simulated user terminal in the area to be deployed for each sub-area based on the network throughput simulation model includes:
simulating the simulated network throughput of each simulated user terminal aiming at each preset deployment position in the to-be-deployed area;
selecting a third preset number of preset deployment positions from the preset deployment positions as effective deployment positions of the simulation user terminals according to the sequence of the simulation network throughput of the simulation user terminals to the preset deployment positions from large to small for each simulation user terminal in the to-be-deployed area;
and calculating the average value of the effective deployment position of the simulated user terminal contained in each sub-area and the simulated network throughput of the simulated user terminal aiming at each simulated user terminal in the to-be-deployed area, and taking the average value as the average simulated network throughput of the simulated user terminal corresponding to each sub-area.
Further, the calculating an average value of the effective deployment location corresponding to the simulated user terminal and the simulated network throughput of the simulated user terminal contained in each sub-region as an average simulated network throughput of the simulated user terminal corresponding to each sub-region includes:
for each sub-area, judging whether the effective deployment position of the simulation user terminal is contained in the sub-area;
if so, calculating an average value of the simulated network throughput of the effective deployment position of the simulated user terminal in the sub-region aiming at the simulated user terminal, and taking the average value as the average simulated network throughput of the sub-region corresponding to the simulated user terminal;
and if not, recording the average network throughput of the sub-area corresponding to the simulated user terminal as zero.
Further, the acquiring the real network throughput of each real user terminal in the area to be deployed for each preset deployment position in the target sub-area includes:
aiming at each preset deployment position in the target sub-area, acquiring the signal intensity of a real user terminal connected with a wireless network base station of the preset deployment position;
and calculating the network throughput corresponding to the preset deployment position and the real user terminal based on the acquired signal intensity and the corresponding relation between the signal intensity and the network throughput aiming at the real user terminal connected with the preset deployed wireless network base station, and taking the network throughput corresponding to the real user terminal and the preset deployment position as the real network throughput corresponding to the real user terminal and the preset deployment position.
Further, the calculating, based on the obtained signal strength and the corresponding relationship between the signal strength and the network throughput, the network throughput corresponding to the preset deployment location and the real user terminal as the real network throughput corresponding to the real user terminal and the preset deployment location includes:
based on the corresponding relationship between the signal strength and the network throughput, calculating to obtain the real network throughput corresponding to the real user terminal and the preset deployment position by adopting the following formula:
Figure BDA0002287060840000031
wherein, C 'represents the real network throughput, the unit of C' is the unit bit/s, H represents the channel bandwidth, the unit of H is Hertz, Signal represents the Signal strength, Nf represents the noise floor, the unit of Nf is dBm, and the value of Nf is-95 dBm at 2.4 GHz.
Selecting a second preset number of preset deployment positions from the preset deployment positions in the target sub-area, and after the second preset number of preset deployment positions are used as the deployment positions of the unmanned aerial vehicle base station, the method further comprises the following steps:
monitoring the number of real user terminals and/or the positions of the real user terminals in the area to be deployed;
and updating the simulation user terminal when the number of the real user terminals and/or the positions of the real user terminals in the area to be deployed are changed.
In order to achieve the above object, an embodiment of the present invention further provides an apparatus for determining a deployment position of an unmanned aerial vehicle base station, where a region to be deployed is divided into a plurality of sub-regions, and the region to be deployed includes a plurality of preset deployment positions, where the apparatus includes:
the simulation module is used for simulating the average simulated network throughput of each simulated user terminal aiming at each sub-region in the to-be-deployed region based on a network throughput simulation model;
a first selecting module, configured to select a first preset number of sub-regions from the sub-regions as target sub-regions according to a descending order of a sum of average simulated network throughputs of the sub-regions, where the sum of average simulated network throughputs of the sub-regions is a sum of average simulated network throughputs of each simulated user terminal for the sub-region in the to-be-deployed region;
an obtaining module, configured to obtain a real network throughput of each real user terminal in the area to be deployed for each preset deployment position in the target sub-area;
the calculation module is used for calculating the sum of the real network throughputs of each real user terminal in the to-be-deployed area aiming at each preset deployment position in the target sub-area, and the sum is used as the sum of the real network throughputs of the preset deployment position;
and the second selection module is used for selecting a second preset number of preset deployment positions from the preset deployment positions in the target sub-area as the deployment positions of the unmanned aerial vehicle base station according to the sequence that the sum of the real network throughputs of all the preset deployment positions in the target sub-area is from large to small.
Further, the simulation module comprises
The simulation submodule is used for simulating the simulation network throughput of each simulation user terminal aiming at each preset deployment position in the to-be-deployed area;
the selection submodule is used for selecting a third preset number of preset deployment positions from the preset deployment positions according to the sequence that the simulation network throughput of the simulation user terminal aiming at the preset deployment positions is from high to low aiming at each simulation user terminal in the area to be deployed and is used as the effective deployment positions of the simulation user terminal;
and the first calculation submodule is used for calculating the average value of the effective deployment position of the simulated user terminal contained in each sub-area and the simulated network throughput of the simulated user terminal aiming at each simulated user terminal in the to-be-deployed area, and the average value is used as the average simulated network throughput of the simulated user terminal corresponding to each sub-area.
Further, the first calculation sub-module is specifically configured to, for each sub-area, determine whether the sub-area contains the effective deployment location of the simulated user terminal; if so, calculating an average value of the simulated network throughput of the effective deployment position of the simulated user terminal in the sub-region aiming at the simulated user terminal, and taking the average value as the average simulated network throughput of the sub-region corresponding to the simulated user terminal; and if not, recording the average network throughput of the sub-area corresponding to the simulated user terminal as zero.
Further, the obtaining module includes:
the acquisition submodule is used for acquiring the signal intensity of a real user terminal connected with the wireless network base station of each preset deployment position in the target subregion;
and the second calculation submodule is used for calculating the network throughput of the preset deployment position and the real user terminal based on the acquired signal intensity and the corresponding relation between the signal intensity and the network throughput as the real network throughput of the real user terminal corresponding to the preset deployment position.
Further, the second calculating sub-module is specifically configured to calculate, based on a corresponding relationship between the signal strength and the network throughput, a real network throughput of the real user terminal corresponding to the preset deployment location by using the following formula:
Figure BDA0002287060840000051
wherein, C 'represents the real network throughput, the unit of C' is the unit bit/s, H represents the channel bandwidth, the unit of H is Hertz, Signal represents the Signal strength, Nf represents the noise floor, the unit of Nf is dBm, and the value of Nf is-95 dBm at 2.4 GHz.
Further, the apparatus further includes:
the monitoring module is used for monitoring whether the number of the real user terminals and/or the positions of the real user terminals in the area to be deployed change or not;
and the updating module is used for updating the simulation user terminal when the number of the real user terminals and/or the positions of the real user terminals in the area to be deployed are changed.
In order to achieve the above object, an embodiment of the present invention provides an electronic device, which includes a processor, a communication interface, a memory, and a communication bus, where the processor and the communication interface are configured to complete communication between the memory and the processor through the communication bus;
a memory for storing a computer program;
and the processor is used for realizing any step of the unmanned aerial vehicle base station deployment position determining method when executing the program stored in the memory.
In order to achieve the above object, an embodiment of the present invention provides a computer-readable storage medium, where a computer program is stored in the computer-readable storage medium, and when executed by a processor, the computer program implements any of the above steps of the method for determining a deployment position of a drone base station.
In order to achieve the above object, an embodiment of the present invention further provides a computer program product containing instructions, which when run on a computer, causes the computer to perform any of the above steps of the method for determining a deployment position of a drone base station.
The embodiment of the invention has the following beneficial effects:
the method for determining the deployment position of the unmanned aerial vehicle base station provided by the embodiment of the invention is based on a network throughput simulation model, simulates the average simulated network throughput of each simulated user terminal in a to-be-deployed area aiming at each sub-area, selects a first preset number of sub-areas from the sub-areas as target sub-areas according to the sequence that the sum of the average simulated network throughputs of the sub-areas is from large to small, obtains the real network throughput of each real user terminal in the to-be-deployed area aiming at each preset deployment position in the target sub-area, calculates the sum of the real network throughputs of each real user terminal in the to-be-deployed area aiming at each preset deployment position in the target sub-area, takes the sum of the real network throughputs of each preset deployment position in the target sub-areas as the sequence that the sum of the real network throughputs of each preset deployment position in the target sub-areas is from large to small, and selecting a second preset number of preset deployment positions from the preset deployment positions in the target sub-area as the deployment positions of the unmanned aerial vehicle base station. By adopting the scheme provided by the embodiment of the invention, the sum of the real network throughputs of all the preset deployment positions in the target sub-area is obtained, and the preset deployment position with the larger corresponding sum of the real network throughputs is selected as the deployment position of the base station of the unmanned aerial vehicle, so that the network throughputs of all users in the target area are improved, and the network quality of the users is improved.
Of course, not all of the advantages described above need to be achieved at the same time in the practice of any one product or method of the invention.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a first flowchart of a method for determining a deployment position of an unmanned aerial vehicle base station according to an embodiment of the present invention;
fig. 2a is a second flowchart of a method for determining a deployment position of an unmanned aerial vehicle base station according to an embodiment of the present invention;
fig. 2b is a flowchart of performing simulated average simulation of network throughput in the method for determining the deployment position of the base station of the unmanned aerial vehicle according to the embodiment of the present invention;
fig. 3a is a schematic structural diagram of a first configuration of an apparatus for determining a deployment position of a base station of an unmanned aerial vehicle according to an embodiment of the present invention;
fig. 3b is a schematic structural diagram of a second configuration of the apparatus for determining a deployment position of a base station of an unmanned aerial vehicle according to an embodiment of the present invention;
fig. 4a is a schematic structural diagram of a simulation module in the apparatus for determining a deployment position of an unmanned aerial vehicle base station according to an embodiment of the present invention;
fig. 4b is a schematic structural diagram of an acquisition module in the unmanned aerial vehicle base station deployment position determining apparatus according to the embodiment of the present invention;
fig. 5 is a schematic structural diagram of an electronic device according to an embodiment of the present invention;
fig. 6 is a schematic diagram of an area to be deployed according to an embodiment of the present invention;
fig. 7 is a schematic diagram of a signal-to-noise ratio generated by simulation of a simulated user terminal corresponding to a preset deployment location based on ray tracing simulation according to an embodiment of the present invention;
fig. 8 is a schematic topographic view of the area to be deployed according to the embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The embodiment of the invention discloses a method for determining deployment positions of unmanned aerial vehicle base stations, wherein a to-be-deployed area is divided into a plurality of sub-areas, the to-be-deployed area comprises a plurality of preset deployment positions, and as shown in figure 1, the method comprises the following steps:
step 101, simulating the average simulated network throughput of each simulated user terminal aiming at each sub-area in the area to be deployed based on a network throughput simulation model.
Step 102, selecting a first preset number of sub-regions from the sub-regions as target sub-regions according to the sequence that the sum of the average simulated network throughputs of the sub-regions is from large to small, wherein the sum of the average simulated network throughputs of the sub-regions is the sum of the average simulated network throughputs of each simulated user terminal aiming at the sub-region in the region to be deployed.
Step 103, acquiring the real network throughput of each real user terminal in the area to be deployed for each preset deployment position in the target sub-area.
And 104, calculating the sum of the real network throughputs of each real user terminal in the to-be-deployed area aiming at each preset deployment position in the target sub-area, and taking the sum as the sum of the real network throughputs of the preset deployment positions.
And 105, selecting a second preset number of preset deployment positions from the preset deployment positions in the target sub-area as the deployment positions of the unmanned aerial vehicle base station according to the sequence that the sum of the real network throughputs of all the preset deployment positions in the target sub-area is from large to small.
By adopting the scheme provided by the embodiment of the invention, the sum of the real network throughput of each preset deployment position in the target sub-area is obtained, and the preset deployment position with the larger corresponding sum of the real network throughput is selected as the deployment position of the unmanned aerial vehicle base station, so that the network throughput requirement of each user in the target area is improved, and the network quality of the user is improved.
The method and apparatus of the present invention will be described in detail with reference to the accompanying drawings using specific embodiments.
In another embodiment of the present invention, as shown in fig. 2a, a method for determining a deployment position of an unmanned aerial vehicle base station according to an embodiment of the present invention may include the following steps:
step 201, based on the network throughput simulation model, simulating the average simulated network throughput of each simulated user terminal for each sub-area in the area to be deployed.
In the embodiment of the invention, the area to be deployed is divided into a plurality of sub-areas, and the area to be deployed comprises a plurality of preset deployment positions.
The area to be deployed is an area where the unmanned aerial vehicle base station is planned to be deployed, and the plurality of preset deployment positions included in the area to be deployed may be a plurality of discrete points predetermined in the area to be deployed, as shown in fig. 6, each discrete point in fig. 6 represents a preset deployment position, where a plane area at a 40m high altitude is a target sub-area a, where a preset deployment position a is marked. The setting of the plurality of preset deployment positions included in the to-be-deployed area can be adapted according to a specific application scene. For example, a square to-be-deployed area with a side length of 40 meters may be divided into a plurality of sub-areas with a side length of 5 meters, and the center of each sub-area is used as a preset deployment position, so that the square to-be-deployed area with a side length of 40 meters may be provided with 64 preset deployment positions.
Step 202, according to the sequence that the sum of the average simulated network throughputs of the sub-regions is from large to small, selecting a first preset number of sub-regions from the sub-regions as a target sub-region, wherein the sum of the average simulated network throughputs of the sub-regions is the sum of the average simulated network throughputs of each simulated user terminal aiming at the sub-region in the region to be deployed.
In this step, the first preset number may be specifically set according to the actual application requirement.
In this step, for each sub-region, a sum of the average simulated network throughput of the sub-region for each simulated user terminal in the sub-region and the to-be-deployed region may be calculated, and the sum is used as the sum of the average simulated network throughput of the sub-region. After the sum of the average simulated network throughputs of each sub-region is obtained, a first preset number of sub-regions can be selected from the sub-regions as target sub-regions according to the sequence from large to small of the sum of the average simulated network throughputs of the sub-regions.
In one possible implementation, a greedy algorithm may be used to select a first preset number of sub-regions as the target sub-regions, for example:
all the simulated user terminals in the area to be deployed may be defined as a set C ═ C1,c2,…,cnThe set of sub-regions of the area to be deployed may be denoted as CH ═ CH1,Ch2,…,ChqAnd selecting a target sub-region based on a greedy algorithm to meet the following conditions:
Figure BDA0002287060840000091
where CH' represents the set of target sub-regions,
Figure BDA0002287060840000092
t (CH') represents the sum of the average simulated network throughputs corresponding to the target sub-region, ET (Ch)l,cj) Represents user cjAnd subregion ChlThe corresponding average simulates the network throughput.
Initial, initial set of target subregions CH' empty, T (CH) executed by the greedy algorithmmaxIs the maximum throughput buffered each time the greedy algorithm is executed to select the target sub-regionOne variable of the sum. As long as the number of elements in the set CH' of target sub-regions is not sufficient for the first preset number, the following target sub-region selection step is performed:
calculating the sum of the average simulated network throughput of each sub-region from the rest sub-region set CH in turn, if the sum of the maximum throughput of the sub-region is more than T (CH)maxThen update T (CH)maxAnd after all the calculation is finished, selecting the sub-region with the maximum sum of the throughputs as the target sub-region selected in the current round, adding the sub-region into the target sub-region set CH', and finishing the current round. And repeating the steps to select the next target sub-region, and stopping executing the greedy algorithm when the number of elements in the set CH 'of the target sub-regions reaches a first preset number to obtain the final set CH' of the target sub-regions.
Step 203, acquiring the real network throughput of each real user terminal in the area to be deployed for each preset deployment position in the target sub-area.
In this step, for each preset deployment position in the target sub-area, the signal strength of the real user terminal connected to the wireless network base station of the preset deployment position can be obtained by monitoring the radio frequency signal sent by the wireless network base station. For example, each real user terminal may monitor the strength of the radio frequency signal sent by the wireless network base station through wireless mon wireless network monitoring software.
For the real user terminal connected to the preset deployed wireless network base station, based on the obtained signal strength and the corresponding relationship between the signal strength and the network throughput, the following formula may be adopted to calculate the network throughput corresponding to the preset deployed position and the real user terminal, as the real network throughput corresponding to the real user terminal and the preset deployed position:
Figure BDA0002287060840000101
wherein, C 'represents the real network throughput, the unit of C' is the unit bit/s, H represents the channel bandwidth, the unit of H is Hertz, Signal represents the Signal strength, Nf represents the noise floor, the unit of Nf is dBm, and the value of Nf is-95 dBm at 2.4 GHz.
In a possible implementation manner, a WiFi AP (wireless fidelity Access Point) may be mounted on the unmanned aerial vehicle, the WiFi AP transmits a radio frequency signal, each real user terminal may monitor the strength of the radio frequency signal through a WirelessMon, and in order to consider as many preset deployment positions with good network quality as possible, the strength of the radio frequency signal may be monitored by allowing the unmanned aerial vehicle to stay at each preset deployment position of the target sub-area for a preset time length for monitoring the strength of the radio frequency signal, for example, allowing the unmanned aerial vehicle to stay at each preset deployment position of the target sub-area for 8 seconds for measurement, and further monitoring the strength of the radio frequency signal. Based on the monitored signal intensity, the method provided by the step can further calculate and obtain the network throughput corresponding to the preset deployment position and the real user terminal in each target sub-area.
Step 204, aiming at each preset deployment position in the target sub-area, calculating a sum of real network throughputs of each real user terminal in the area to be deployed aiming at the preset deployment position, and taking the sum as the sum of the real network throughputs of the preset deployment position.
In this step, a wireless network base station at one preset deployment position may connect a plurality of user terminals, for example, for a preset deployment position a in a target sub-area as shown in fig. 6, there are 5 real user terminals connected to a, and a sum of real network throughputs of the 5 real user terminals for the preset deployment position a and the real network throughputs is calculated as a sum of real network throughputs of the preset deployment position a.
Step 205, selecting a second preset number of preset deployment positions from the preset deployment positions in the target sub-area as the deployment positions of the unmanned aerial vehicle base station according to the sequence from large to small of the sum of the real network throughputs of each preset deployment in the target sub-area.
In steps 204 and 205, a greedy algorithm may be adopted, and a second preset number of preset deployment positions are selected as the deployment positions of the base station of the unmanned aerial vehicle by calculating a sum of real network throughputs of real user terminals in the area to be deployed for the preset deployment positions. The calculation principle using the greedy algorithm is described in detail in step 202, and will not be described herein.
In this step, the second preset number may be specifically set according to an actual application situation. For example, when the number of the preset deployments of the target sub-area is 100, the 100 preset deployments are sequenced according to the sequence from the large sum to the small sum of the corresponding real network throughputs, and when 5 unmanned aerial vehicle base stations need to be deployed according to actual requirements, the first 5 preset deployment positions can be selected from the sequencing result of the sum of the real network throughputs to serve as the deployment positions of the unmanned aerial vehicle base stations.
Step 206, determining whether the real ue changes, if yes, executing step 207, and if no, executing step 208.
In the step, whether the real user terminal changes or not can be judged by monitoring the number and/or the position of the real user terminal in the area to be deployed, and when the number and/or the position of the real user terminal in the area to be deployed are monitored to change, the real user terminal changes; when the number of the real user terminals in the area to be deployed and the position of the real user terminals are monitored to be unchanged, the real user terminals are not changed.
Step 207, updating the simulated user terminal, and then returning to execute step 201.
And step 208, deploying the unmanned aerial vehicle base station at the determined deployment position of the unmanned aerial vehicle base station.
By adopting the scheme provided by the embodiment of the invention, the real network throughput of each preset deployment position in the target sub-area is obtained, the sum of the real network throughputs of each preset deployment position in the target sub-area is calculated, and the corresponding preset deployment position with the large sum of the real network throughputs is selected as the deployment position of the unmanned aerial vehicle base station, so that the network throughput of each user in the target area is improved, and the network quality of the user is improved.
In the implementation of the present invention, as shown in fig. 2b, based on the network throughput simulation model, a specific simulation process for simulating an average simulated network throughput of each simulated user terminal for each sub-area in the area to be deployed may include:
step 201 a: and simulating the simulated network throughput of each simulated user terminal aiming at each preset deployment position in the to-be-deployed area.
In one possible implementation, the simulation network throughput of each simulation user terminal for each preset deployment position in the area to be deployed can be simulated by using the Wireless instate complex electromagnetic environment modeling simulation analysis software. The topographic map of the area to be deployed can be input into Wireless instate software, and the simulated network throughput corresponding to each user terminal and each preset deployment position can be calculated through the signal-to-noise ratio corresponding to each simulated user terminal and each preset deployment position and the corresponding relation between the signal-to-noise ratio and the network throughput, which are obtained by the Wireless instate software.
In one possible embodiment, the topographic map of the area to be deployed as shown in fig. 8 may be input into Wireless suite software, and the Wireless suite software may transmit an analog rf signal at the location of each analog user terminal in the area to be deployed. The analog user terminal location, as represented by c1-c7 shown in fig. 8, may transmit analog radio frequency signals, for example, for the c1 location. When the transmitted analog signal reaches each preset deployment position, for example, each preset deployment position shown in fig. 6, the signal intensity is attenuated due to the reflection, refraction and diffraction of the analog signal by various objects in the region to be deployed, and the attenuation degrees of the analog signal are different for different reached preset deployment positions, that is, each preset deployment position corresponds to a different signal attenuation degree. Based on different signal attenuation degrees corresponding to each preset deployment position, the signal-to-noise ratio of the simulated radio-frequency signal reaching each preset deployment position can be calculated through Wireless instate software and is used as the signal-to-noise ratio of the preset deployment position to the simulated user terminal. As shown in FIG. 7, a signal-to-noise ratio thermodynamic diagram generated by ray tracing simulation of a simulated user terminal can be obtained through the Wireless instance software. Based on the obtained corresponding relationship between the signal-to-noise ratio and the network throughput, the simulated network throughput corresponding to the simulated user terminal and the preset deployment position can be obtained by calculation by adopting the following formula:
Figure BDA0002287060840000121
h represents the channel bandwidth, the unit of H is Hertz, C represents the analog network throughput, the unit of C is the unit bit/s, and SNR represents the signal-to-noise ratio.
By the method, the simulated network throughput corresponding to each preset deployment position of each simulated user terminal in the to-be-deployed area can be obtained.
Step 201 b: and selecting a third preset number of preset deployment positions from the preset deployment positions as effective deployment positions of the simulation user terminals according to the sequence of the simulation user terminals from large to small in simulation network throughput aiming at the preset deployment positions.
In this step, the third preset number may be specifically determined according to the actual application. For example, for each simulated user terminal in the area to be deployed, the simulated network throughputs of the simulated user terminals for the preset deployment positions are sorted from large to small, and the effective deployment position corresponding to the simulated user terminal at the preset deployment position corresponding to the first 10% of the simulated network throughput in the sorting result can be selected. Similarly, the effective deployment location of each simulated user terminal can be obtained in this step.
Step 201 c: and for each sub-area, judging whether the sub-area contains the effective deployment position of the simulation user terminal, if so, executing the step 201d, and if not, executing the step 201 e.
Step 201d, calculating an average value of the simulated network throughput of the effective deployment position of the simulated user terminal contained in the sub-area for the simulated user terminal, as an average simulated network throughput corresponding to the sub-area and the simulated user terminal.
Step 201e, recording the average network throughput of the sub-area corresponding to the simulated user terminal as zero.
In the embodiment of the invention, one or more target sub-areas capable of meeting the network throughput requirement of each simulation user in the area to be deployed are further selected from each sub-area by simulating the simulation network throughput of each preset deployment position in the area to be deployed aiming at each simulation user terminal, so as to obtain the real network throughput of each preset deployment position in the target sub-area, and the preset deployment position with the corresponding large sum of the real network throughput is selected as the base station deployment position of the unmanned aerial vehicle by calculating the sum of the real network throughputs of each preset deployment position in the target sub-area, so that the network throughput of each user in the target area is improved, and the network quality of the user is improved. And the time for determining the deployment position of the unmanned aerial vehicle base station is saved by using a ray tracing simulation method.
Based on the same inventive concept, according to the method for determining the deployment position of the base station of the unmanned aerial vehicle provided in the above embodiment of the present invention, correspondingly, another embodiment of the present invention further provides a device for determining the deployment position of the base station of the unmanned aerial vehicle, a schematic structural diagram of which is shown in fig. 3a, specifically including:
the simulation module 301 is configured to simulate, based on a network throughput simulation model, an average simulated network throughput of each simulated user terminal for each sub-area in the area to be deployed;
a first selecting module 302, configured to select a first preset number of sub-regions from the sub-regions as target sub-regions according to a descending order of a sum of average simulated network throughputs of the sub-regions, where the sum of average simulated network throughputs of the sub-regions is a sum of average simulated network throughputs of each simulated user terminal for the sub-region in the region to be deployed;
an obtaining module 303, configured to obtain a real network throughput of each real user terminal in the area to be deployed for each preset deployment position in the target sub-area;
a calculating module 304, configured to calculate, for each preset deployment position in the target sub-region, a sum of real network throughputs of each real user terminal in the to-be-deployed region for the preset deployment position, where the sum is used as the sum of the real network throughputs of the preset deployment position;
a second selecting module 305, configured to select, from the preset deployment positions in the target sub-area, a second preset number of preset deployment positions as the deployment positions of the base station of the unmanned aerial vehicle in the order that the sum of the actual network throughputs of the preset deployment positions in the target sub-area is from large to small.
Therefore, by adopting the device provided by the embodiment of the invention, the sum of the real network throughputs of all the preset deployment positions in the target sub-area is obtained, and the preset deployment position with the larger corresponding sum of the real network throughputs is selected as the deployment position of the unmanned aerial vehicle base station, so that the network throughputs of all users in the target area are improved, and the network quality of the users is improved.
Further, as shown in fig. 4a, the simulation module 301 includes:
the simulation submodule 401 is configured to simulate a simulation network throughput of each simulation user terminal for each preset deployment position in the area to be deployed;
a selecting submodule 402, configured to select, for each simulated user terminal in the area to be deployed, a third preset number of preset deployment positions from the preset deployment positions in order that the simulated network throughput of the simulated user terminal for the preset deployment positions is from high to low, as effective deployment positions of the simulated user terminal;
the first calculating submodule 403 is configured to calculate, for each simulated user terminal in the area to be deployed, an average value of the effective deployment position of the simulated user terminal contained in each sub-area and the simulated network throughput of the simulated user terminal, as an average simulated network throughput of the simulated user terminal corresponding to each sub-area.
Further, as shown in fig. 4a, the first calculating submodule 403 is specifically configured to determine, for each sub-area, whether the sub-area includes an effective deployment position of the simulated user terminal; if so, calculating an average value of the simulated network throughput of the effective deployment position of the simulated user terminal in the sub-region aiming at the simulated user terminal, and taking the average value as the average simulated network throughput of the sub-region corresponding to the simulated user terminal; if not, recording the average network throughput of the sub-area corresponding to the simulated user terminal as zero
Further, as shown in fig. 4b, the obtaining module 303 includes:
an obtaining submodule 404, configured to obtain, for each preset deployment position in the target sub-area, a signal strength of a real user terminal connected to the wireless network base station at the preset deployment position;
a second calculating submodule 405, configured to calculate, for a real user terminal connected to the preset deployed wireless network base station, a network throughput corresponding to the preset deployment position and the real user terminal based on the obtained signal strength and a corresponding relationship between the signal strength and the network throughput, and use the network throughput as the real network throughput corresponding to the real user terminal and the preset deployment position.
Further, as shown in fig. 4b, the second calculating sub-module 405 is specifically configured to calculate, based on the corresponding relationship between the signal strength and the network throughput, a real network throughput of the real user terminal corresponding to the preset deployment location by using the following formula:
Figure BDA0002287060840000151
wherein, C 'represents the real network throughput, the unit of C' is the unit bit/s, H represents the channel bandwidth, the unit of H is Hertz, Signal represents the Signal strength, Nf represents the noise floor, the unit of Nf is dBm, and the value of Nf is-95 dBm at 2.4 GHz.
Further, as shown in fig. 3b, the apparatus for determining a deployment position of a base station of an unmanned aerial vehicle further includes:
a monitoring module 306, configured to monitor whether the number of real user terminals and/or the positions of the real user terminals in the area to be deployed change;
an updating module 307, configured to update the simulation user terminal when the number of the real user terminals and/or the position of the real user terminal in the area to be deployed changes.
Based on the same inventive concept, according to the method for determining the deployment position of the base station of the unmanned aerial vehicle provided by the above embodiment of the present invention, correspondingly, another embodiment of the present invention further provides an electronic device, referring to fig. 5, the electronic device according to the embodiment of the present invention includes a processor 501, a communication interface 502, a memory 503 and a communication bus 504, wherein the processor 501, the communication interface 502 and the memory 503 complete mutual communication through the communication bus 504.
A memory 503 for storing a computer program;
the processor 501, when executing the program stored in the memory 503, implements the following steps:
simulating the average simulated network throughput of each simulated user terminal aiming at each sub-area in the area to be deployed based on a network throughput simulation model;
according to the sequence that the sum of the average simulated network throughputs of the sub-areas is from large to small, selecting a first preset number of sub-areas from the sub-areas as a target sub-area, wherein the sum of the average simulated network throughputs of the sub-areas is the sum of the average simulated network throughputs of each simulated user terminal in the area to be deployed for the sub-area;
acquiring the real network throughput of each real user terminal in the to-be-deployed area aiming at each preset deployment position in the target sub-area;
calculating the sum of the real network throughput of each real user terminal in the to-be-deployed area aiming at each preset deployment position in the target sub-area, wherein the sum is used as the sum of the real network throughput of the preset deployment position;
and selecting a second preset number of preset deployment positions from the preset deployment positions in the target sub-area as the deployment positions of the unmanned aerial vehicle base station according to the sequence from large to small of the sum of the real network throughputs of all the preset deployment positions in the target sub-area.
The communication bus mentioned in the electronic device may be a Peripheral Component Interconnect (PCI) bus, an Extended Industry Standard Architecture (EISA) bus, or the like. The communication bus may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, only one thick line is shown, but this does not mean that there is only one bus or one type of bus.
The communication interface is used for communication between the electronic equipment and other equipment.
The Memory may include a Random Access Memory (RAM) or a Non-Volatile Memory (NVM), such as at least one disk Memory. Optionally, the memory may also be at least one memory device located remotely from the processor.
The Processor may be a general-purpose Processor, including a Central Processing Unit (CPU), a Network Processor (NP), and the like; but also Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field Programmable Gate Arrays (FPGAs) or other Programmable logic devices, discrete Gate or transistor logic devices, discrete hardware components.
In yet another embodiment of the present invention, a computer-readable storage medium is further provided, in which a computer program is stored, and the computer program, when executed by a processor, implements the steps of any of the foregoing methods for determining a deployment position of a drone base station.
In a further embodiment provided by the present invention, there is also provided a computer program product containing instructions which, when run on a computer, cause the computer to perform any of the drone base station deployment location determination methods of the above embodiments.
In the above embodiments, the implementation may be wholly or partially realized by software, hardware, firmware, or any combination thereof. When implemented in software, may be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When loaded and executed on a computer, cause the processes or functions described in accordance with the embodiments of the invention to occur, in whole or in part. The computer may be a general purpose computer, a special purpose computer, a network of computers, or other programmable device. The computer instructions may be stored in a computer readable storage medium or transmitted from one computer readable storage medium to another, for example, from one website site, computer, server, or data center to another website site, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, Digital Subscriber Line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device, such as a server, a data center, etc., that incorporates one or more of the available media. The usable medium may be a magnetic medium (e.g., floppy Disk, hard Disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., Solid State Disk (SSD)), among others.
It is noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
All the embodiments in the present specification are described in a related manner, and the same and similar parts among the embodiments may be referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, as for the device, the electronic apparatus and the storage medium embodiments, since they are substantially similar to the method embodiments, the description is relatively simple, and the relevant points can be referred to the partial description of the method embodiments.
The above description is only for the preferred embodiment of the present invention, and is not intended to limit the scope of the present invention. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention shall fall within the protection scope of the present invention.

Claims (8)

1. A method for determining deployment positions of unmanned aerial vehicle base stations is characterized in that a region to be deployed is divided into a plurality of sub-regions, the region to be deployed comprises a plurality of preset deployment positions, and the method comprises the following steps:
simulating the average simulated network throughput of each simulated user terminal aiming at each sub-area in the area to be deployed based on a network throughput simulation model;
according to the sequence that the sum of the average simulated network throughputs of the sub-areas is from large to small, selecting a first preset number of sub-areas from the sub-areas as a target sub-area, wherein the sum of the average simulated network throughputs of the sub-areas is the sum of the average simulated network throughputs of each simulated user terminal in the area to be deployed for the sub-area;
acquiring the real network throughput of each real user terminal in the to-be-deployed area aiming at each preset deployment position in the target sub-area;
calculating the sum of the real network throughput of each real user terminal in the to-be-deployed area aiming at each preset deployment position in the target sub-area, wherein the sum is used as the sum of the real network throughput of the preset deployment position;
according to the sequence from large to small of the sum of the real network throughputs of all the preset deployment positions in the target sub-area, selecting a second preset number of preset deployment positions from the preset deployment positions in the target sub-area as the deployment positions of the unmanned aerial vehicle base station;
the simulating the average simulated network throughput of each simulated user terminal aiming at each sub-area in the area to be deployed based on the network throughput simulation model comprises:
simulating the simulated network throughput of each simulated user terminal aiming at each preset deployment position in the to-be-deployed area;
selecting a third preset number of preset deployment positions from the preset deployment positions as effective deployment positions of the simulation user terminals according to the sequence of the simulation network throughput of the simulation user terminals to the preset deployment positions from large to small for each simulation user terminal in the to-be-deployed area;
and calculating the average value of the effective deployment position of the simulated user terminal contained in each sub-area and the simulated network throughput of the simulated user terminal aiming at each simulated user terminal in the to-be-deployed area, and taking the average value as the average simulated network throughput of the simulated user terminal corresponding to each sub-area.
2. The method of claim 1, wherein calculating an average of the effective deployment location corresponding to the simulated user terminal and the simulated network throughput of the simulated user terminal contained in each of the sub-regions as an average simulated network throughput of the simulated user terminal corresponding to each of the sub-regions comprises:
for each sub-area, judging whether the effective deployment position of the simulation user terminal is contained in the sub-area;
if so, calculating an average value of the simulated network throughput of the effective deployment position of the simulated user terminal in the sub-region aiming at the simulated user terminal, and taking the average value as the average simulated network throughput of the sub-region corresponding to the simulated user terminal;
and if not, recording the average network throughput of the sub-area corresponding to the simulated user terminal as zero.
3. The method according to claim 1, wherein the obtaining the real network throughput of each real user terminal in the area to be deployed for each preset deployment position in the target sub-area comprises:
aiming at each preset deployment position in the target sub-area, acquiring the signal intensity of a real user terminal connected with a wireless network base station of the preset deployment position;
and calculating the network throughput corresponding to the preset deployment position and the real user terminal based on the acquired signal intensity and the corresponding relation between the signal intensity and the network throughput aiming at the real user terminal connected with the preset deployed wireless network base station, and taking the network throughput corresponding to the real user terminal and the preset deployment position as the real network throughput corresponding to the real user terminal and the preset deployment position.
4. The method according to claim 3, wherein calculating, based on the obtained signal strength and the corresponding relationship between the signal strength and the network throughput, the network throughput corresponding to the preset deployment location and the real user terminal as the real network throughput corresponding to the real user terminal and the preset deployment location comprises:
based on the corresponding relationship between the signal strength and the network throughput, calculating to obtain the real network throughput corresponding to the real user terminal and the preset deployment position by adopting the following formula:
Figure FDA0003179382200000021
wherein, C' represents the real network throughput, the unit of C is bit/s, H represents the channel bandwidth, the unit of H is Hertz, Signal represents the Signal strength, Nf represents the noise floor, the unit of Nf is dBm, and the value of Nf is-95 dBm at 2.4 GHz.
5. The method according to any one of claims 1 to 4, wherein after selecting a second preset number of preset deployment positions from the preset deployment positions in the target sub-area as the deployment positions of the drone base station, the method further comprises:
monitoring the number of real user terminals and/or the positions of the real user terminals in the area to be deployed;
and updating the simulation user terminal when the number of the real user terminals and/or the positions of the real user terminals in the area to be deployed are changed.
6. An unmanned aerial vehicle base station deployment position determining device is characterized in that a region to be deployed is divided into a plurality of sub-regions, the region to be deployed comprises a plurality of preset deployment positions, and the device comprises:
the simulation module is used for simulating the average simulated network throughput of each simulated user terminal aiming at each sub-region in the to-be-deployed region based on a network throughput simulation model;
a first selecting module, configured to select a first preset number of sub-regions from the sub-regions as target sub-regions according to a descending order of a sum of average simulated network throughputs of the sub-regions, where the sum of average simulated network throughputs of the sub-regions is a sum of average simulated network throughputs of each simulated user terminal for the sub-region in the to-be-deployed region;
an obtaining module, configured to obtain a real network throughput of each real user terminal in the area to be deployed for each preset deployment position in the target sub-area;
the calculation module is used for calculating the sum of the real network throughputs of each real user terminal in the to-be-deployed area aiming at each preset deployment position in the target sub-area, and the sum is used as the sum of the real network throughputs of the preset deployment position;
the second selection module is used for selecting a second preset number of preset deployment positions from the preset deployment positions in the target sub-area as the deployment positions of the unmanned aerial vehicle base station according to the sequence that the sum of the real network throughputs of all the preset deployment positions in the target sub-area is from large to small;
the simulation module comprises
The simulation submodule is used for simulating the simulation network throughput of each simulation user terminal aiming at each preset deployment position in the to-be-deployed area;
the selection submodule is used for selecting a third preset number of preset deployment positions from the preset deployment positions according to the sequence that the simulation network throughput of the simulation user terminal aiming at the preset deployment positions is from high to low aiming at each simulation user terminal in the area to be deployed and is used as the effective deployment positions of the simulation user terminal;
and the first calculation submodule is used for calculating the average value of the effective deployment position of the simulated user terminal contained in each sub-area and the simulated network throughput of the simulated user terminal aiming at each simulated user terminal in the to-be-deployed area, and the average value is used as the average simulated network throughput of the simulated user terminal corresponding to each sub-area.
7. The apparatus according to claim 6, wherein the first computing sub-module is specifically configured to determine, for each of the sub-areas, whether the sub-area contains the valid deployment location of the simulated user terminal; if so, calculating an average value of the simulated network throughput of the effective deployment position of the simulated user terminal in the sub-region aiming at the simulated user terminal, and taking the average value as the average simulated network throughput of the sub-region corresponding to the simulated user terminal; and if not, recording the average network throughput of the sub-area corresponding to the simulated user terminal as zero.
8. The apparatus of claim 6, wherein the obtaining module comprises:
the acquisition submodule is used for acquiring the signal intensity of a real user terminal connected with the wireless network base station of each preset deployment position in the target subregion;
and the second calculation submodule is used for calculating the network throughput of the preset deployment position and the real user terminal based on the acquired signal intensity and the corresponding relation between the signal intensity and the network throughput as the real network throughput of the real user terminal corresponding to the preset deployment position.
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