CN109413664A - A kind of super-intensive based on interference is tethered at unmanned plane base station height adjusting method - Google Patents
A kind of super-intensive based on interference is tethered at unmanned plane base station height adjusting method Download PDFInfo
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Abstract
The invention discloses a kind of super-intensives based on interference to be tethered at unmanned plane base station height adjusting method, for being in the communication link of the multiple no-manned plane of same frequency range, establish interference channel mean field betting model, based on group's state averagely come describe with other members interact dynamical equation, update to obtain the optimum control of height adjustment speed by continuous iteration；The present invention obtains all unmanned plane base stations that are tethered to certain caused by user security risk and interference signal intensity in the method for mean field approximation, by obtaining optimum control i.e. velocity vector from system equation, the optimal height regulation scheme for deriving each unmanned plane shows all behavioural characteristics for being tethered at unmanned plane base station under different conditions in the control period by numerical result.
Description
[technical field]
The invention belongs to wireless communication technology fields, and in particular to a kind of super-intensive based on interference is tethered at unmanned plane base station
Height adjusting method.
[background technique]
In recent years, as the evolution of mobile radio system develops, UAV Communication is at home and abroad caused widely
Research concern.The exclusive feature of unmanned plane itself can efficiently solve terrestrial cells base station in traditional communication can not quick portion
Many problems such as affix one's name to, involve great expense, is poor to special screne adaptability.Therefore, unmanned plane can be by carrying base station module
Unit is disposed as air base station, further realizes the communication overlay function of ground Hot Spot.Compared to traditional fixed base
It stands the network coverage, Communication Network for UAVS has the irreplaceable advantages such as maneuverability, thus various in military and civilian etc.
There is huge application potential in field.The unmanned plane that can be used for air communication base station carrier is many kinds of, and in practical applications,
Being tethered at unmanned plane, this is a kind of with special power-supply system, specific customization cable power supply and transmission, can under certain loads for a long time
The aerial platform of hovering suffers from more favors.Be tethered at unmanned plane formula have it is easy to carry, open up it is rapid, easy to operate
Feature is, it can be achieved that a wide range of communication overlay.According to the fixation position difference of winch can be divided into fixed ground, vehicle-mounted removable and
Three kinds of working methods of Portable are to adapt to the demands of various working environments.
However, in terms of using unmanned plane progress subsidiary communications is tethered at, there are also many problems, in intensive unmanned plane base station net
In network, user suffers from the common-channel interference of other base stations, and how to realize that effective interference controls in unmanned plane base station end is
One challenging problem.In unmanned plane air-to-ground communication, the big key for influencing communication quality is channel condition,
According to the advantage in the power supply and control that are tethered at unmanned plane, be able to carry out more in real time highly control come to channel condition into
Row is adjusted, so that its communication quality for meeting serviced user.And when user is in super-intensive unmanned plane base station network,
Unavoidably will receive the interference signal from other unmanned plane base stations, interference signal intensity affects the communication quality of user,
The base station for servicing the user should carry out corresponding control according to active user's interference environment to meet user communication quality.
Such as in " Drone small cells in the clouds:Design, the deployment and of document 1
performance analysis[IEEE Global Communications Conference(GLOBECOM)San
Diego, CA, Dec.2015] low latitude platform is considered in ", have studied the downlink covering performance of unmanned plane cellulor.In addition,
Each unmanned plane cellulor can calculate its optimum height.
" the Placement optimization of UAV-mounted mobile base stations [IEEE of document 2
Commun.Lett., vol.21, no.3, pp.604-607, Mar.2017] " consider unmanned plane base station the optimal position 3D rule
The problem of drawing carrys out maximization network efficiency.However require that by global context information provided by ground control station is collected.
" the 3-D Placement of an unmanned aerial vehicle base station (UAV- of document 3
BS)for energy-efficient maximal coverage[IEEE Wireless Comm.Lett.,,vol.6,
No.4, pp.434-437, Aug.2017.] " it proposes one kind unmanned plane base station communication is made to cover the positioning of maximized position and calculate
Method.Similarly, this method also relies on global information.
Patent publication No. is in 108092729 A of CN, and inventor devises a kind of UAV Communication jamproof system, mentions
The anti-interference model in UAV Communication and a kind of Staenberg game gradient algorithm are gone out.Inventor relies on the algorithm, makes
Unmanned plane when being communicated with user, intelligent jammer adjusts its own transimission power according to the transimission power of unmanned plane user
To optimal, power control of the user further according to jamming power adjustment progress itself；The two cycle alternation is until unmanned plane is used
Family and intelligent jammer converge to optimal transmission power.Its using the power control of conventional cellular communication system mode
Come the control interfered, the moveable advantage in unmanned plane base station is not embodied.
[summary of the invention]
The object of the present invention is to provide a kind of super-intensives based on interference to be tethered at unmanned plane base station height adjusting method, with solution
Certainly communication quality difference and the low problem of energy efficiency under super-intensive network.
The invention adopts the following technical scheme: a kind of super-intensive based on interference is tethered at unmanned plane base station height adjustment side
Method, the communication link of the multiple no-manned plane for being in same frequency range establish interference channel mean field betting model, are based on group's shape
State averagely describes the dynamical equation to interact with other members, updates to obtain height adjustment speed most by continuous iteration
Excellent control.
Further, it follows the steps below to implement:
Step 1: building system model:
System model is unmanned plane base station set, is used It indicates, N number of unmanned plane base station
The same channel is shared simultaneously carries out downlink data transmission；
Step 2: carrying out mean field approximation to interference channel: before the control period starts, setting all unmanned plane base stations
Transmission power calculates being averaged for interference according to the interfering signal power that the serviced user's receiving terminal in unmanned plane base station receives
Channel；
Step 3: establishing cost function: using the speed on unmanned plane vertical direction as motion space, being believed according to communication link
It makes an uproar than constructing corresponding cost function with unmanned plane energy consumption, making one asks the smallest optimization of long run average cost function
Topic, according to certain weight ratio, acquires optimal joint Power and rate control, so that long run cost function obtains minimum value.
Further, the specific method of mean field approximation is in step 2:
Before the control period starts, set the transmission powers of all unmanned plane base stations asThe average channel of interference is are as follows:
Wherein, k represents unmanned plane base station k；U represents some channel that unmanned aerial vehicle group is used in conjunction with；Represent nothing
The interfering signal power that man-machine the serviced user's receiving terminal of base station k receives,It is all in addition to the k of unmanned plane base station
The same frequency power signal that unmanned plane base station is transmitted；N represents unmanned plane base station number in intensive unmanned plane base station network；Represent generation
The average emitted power for the unmanned plane base station in addition to k that table interferes；hjRepresent the height of unmanned plane base station j；When t is represented
Between；Represent the average ground projector distance between user terminal and other interference unmanned plane base stations to be asked；
The wherein function f in formula (1) are as follows:
Wherein, h represents the height of unmanned plane base station；It represents between user terminal and other interference unmanned plane base stations to be asked
Average ground projector distance；α represents channel path loss coefficient；η represents non line-of-sight communication channel fading coefficient；B and C is represented
Constant.
Further, cost function is established in step 3 detailed process is as follows,
Signal to Interference plus Noise Ratio by taking the user of unmanned plane base station k as an example, in receiving end are as follows:
Wherein, λk(t) Signal to Interference plus Noise Ratio of unmanned plane base station k is represented；Pr,k,kRepresent the power of received useful signal；Iu,k
(t) practical received interfering signal power is represented；N0Represent noise；
The wherein P in formula (3)r,k,kFor,
Pr,k,k=PLoSPk|Xk,k|-α+PNLoSηPk|Xk,k|-α, (4),
Wherein, PLoSAnd PNLoSRepresent communication channel whether be horizon communication probability；Xk,kRepresent unmanned plane base station k and its
Linear distance between user；PkRepresent the transmission power of unmanned plane base station k；α represents channel path loss coefficient；η represents non-view
Away from communication channel attenuation coefficient；Xk,kRepresent the linear distance between the user of unmanned plane base station k and unmanned plane base station k.
The totle drilling cost function of unmanned plane base station k by user communication quality and energy loss adduction gained, therefore by formula (1) and
Formula (4) brings formula (3) into and obtains the totle drilling cost function of unmanned plane base station k:
Wherein, ck(t, h) represents the totle drilling cost function of unmanned plane base station k；ω1And ω2Weighted factor is represented, so that two
Cost function is in a dimension；Represent the average emitted power of the unmanned plane base station in addition to k interfered；m(t,h)
Represent mean field item；D represents differential operator；The second order term of representation speed, for measuring unmanned plane because height change is made
At additional energy consumption.
Compared with prior art, the present invention at least has the advantages that
1, it is intensive to model this by more member's mean field game frameworks under a continuous time state by the present invention
Mutual interference environment under network, it is contemplated that super-intensive is tethered at the mutual interference problem in unmanned plane base station communication network, substantially reduces
Computation complexity.
2, the corresponding system equation for the mean field game framework that the present invention establishes, including system dynamical equation and relevant cost
Function enables final gained scheme effectively to promote network performance.
3, the present invention obtains all unmanned plane base stations that are tethered to certain caused by user security risk and interference in the method for mean field approximation
Signal strength improves realizability.
4, the present invention derives the optimal of each unmanned plane by obtaining optimum control i.e. velocity vector from system equation
Height adjustment scheme, gained scheme are more rigorous.
5, the present invention shows that all unmanned plane base stations that are tethered at are under different conditions in the control period by numerical result
Behavioural characteristic acts not only as the scheme of practical operation, or other decisions make behavior prediction reference.
[Detailed description of the invention]
Fig. 1 is the present invention according to scene model built figure；
Fig. 2 is that all member conditions of the invention initial are that equilibrium state under being uniformly distributed is averaged field distribution；
Fig. 3 is that equilibrium state of the present invention is averaged the sectional view of field distribution；
Fig. 4 is that initial all member conditions of the invention are to be uniformly distributed the optimal height control program of lower member；
Fig. 5 is the present invention point of average Signal to Interference plus Noise Ratio level at any time in obtained optimum control scheme lower network
Cloth.
[specific embodiment]
Below by drawings and examples, technical scheme of the present invention will be described in further detail.
The invention discloses a kind of super-intensives based on interference to be tethered at unmanned plane base station height adjusting method, for unmanned plane
As the intensive unmanned plane downlink communication system of aerial mobile base station, these intensive unmanned planes are in same frequency range, i.e., for
It is in the communication link of the multiple no-manned plane of same frequency range, the influence of unmanned plane energy consumption is considered, establishes mean field betting model,
Mean field approximation method is proposed to obtain the average channel that user terminal is disturbed, is established about communication quality and energy consumption
Cost function, problem was modeled as asking in the control period cost function is made it is expected the smallest optimal control problem, and derived phase
System of random differential equations is closed, the optimal height control method of aerial unmanned plane base station is acquired using finite difference calculus.
Step 1: building system model:
System model is unmanned plane base station set, is used It indicates, N number of unmanned plane base station
The same channel is shared simultaneously carries out downlink data transmission.
System model disclosed in this invention is the unmanned plane cell communication network of a super-intensive, wherein a large amount of unmanned planes
Air to surface downlink communication service is provided as air base station, a large amount of autonomous unmanned planes are by random placement in limited a wide range of area
In domain, user can attempt to carry out link connection with corresponding unmanned plane by maximum pilot signal.Define unmanned plane base station set
With It indicates, which shares the same channel simultaneously and carry out downlink data biography
It is defeated；Assuming that the N number of unmanned plane base that can be serviced a user given one unmanned plane base station of period, and be considered
It stands while sharing the same channel and carry out downlink data transmission.As shown in Figure 1, the unmanned plane base station carrier in the scene considered
It to be tethered at unmanned plane, is made of aerial platform and ground carrier vehicle, centre is connected by cable, for carrier to aerial platform
It powers and communicates.Therefore, the method for optimally controlling of its high altitude platform height adjustment is proposed based on such framework.
By taking the k of unmanned plane base station as an example, user is by the dry of the homogenous frequency signal transmitted from every other unmanned plane base station
It disturbs, if interference signal increases, in order to meet communication performance, unmanned plane base station k can be by the adjusting of height so that receiving end has
It is improved with signal power, and such that it causes bigger interference to the user of other unmanned plane base stations.Therefore, when nobody
When machine base station number increases, i.e. when N → ∞, needing to formulate a control law makes whole system performance reach more preferable.It is being mentioned
In scene out, the height adjustment of unmanned plane base station k is considered as state space, is influenced between unmanned plane base station and its service user
The speed of distance is considered as control.
In the interference model under dense network, the communication link of the base station and user of locating same frequency range is considered as member,
State in the dynamical system of each member is the present level of unmanned plane base station, and it has impact on its communication letters to all users
Road condition, and behavior is then the height adjustment speed of unmanned plane base station, in a given period of time T, different nobody
Machine has different elemental heights, the state equation of dynamic control are as follows:
dhk(t)=vk(t)dt+σtdWi(t), (6),
Wherein, hk(t) height of unmanned plane base station k is represented；vk(t) speed of vertical direction is represented；D represents differential operator；
vkIt (t) is all continuous time-varying, Wi(t) Brownian movement for meeting independent micro-nano process, σ are representedtInterference coefficient is represented,
Differential meets Ito formula.Under the definition of above-mentioned state space, each unmanned plane base station k is it needs to be determined that a method in optimal control
ThenMake long-term downlink connect into power by the long-term individual cost of minimum and reaches maximum.
Step 2: carrying out mean field approximation to interference channel: before the control period starts, setting all unmanned plane base stations
Transmission power calculates being averaged for interference according to the interfering signal power that the serviced user's receiving terminal in unmanned plane base station receives
Channel.
All unmanned plane base stations that are tethered at are obtained to certain caused by user security risk and interference signal intensity in the method for mean field approximation,
Realizability is improved, before the control period starts, all unmanned plane base stations are adjusted to identical transmission power, all user's measurements
Receiving end signal intensity, by the known channel condition by between service user and unmanned plane base station, then every other user's interference
The average channel conditions of channel can obtain by formula, set the transmission powers of all unmanned plane base stations asThat so interferes is flat
Equal channel can be obtained by formula:
Wherein, k represents unmanned plane base station k；U represents some channel that unmanned aerial vehicle group is used in conjunction with；Represent nothing
The interfering signal power that man-machine the serviced user's receiving terminal of base station k receives, thereforeBe it is all except unmanned plane base station k with
The same frequency power signal that outer unmanned plane base station is transmitted；Pr,j,kThe user for representing unmanned plane base station k receives unmanned plane base station j biography
The signal power come；Represent the average emitted power of the unmanned plane base station in addition to k interfered；N is close to be considered
Collect unmanned plane base station number in unmanned plane base station network, soIt equally can be approximated to be N-1 and possess same disturbance channel
The same frequency power signal that the unmanned plane channel of condition transmits；hjRepresent the height of unmanned plane base station j；T represents the time；rj,kIt represents
Floor projection distance between unmanned plane base station j and unmanned plane base station k current service user；Represent user terminal to be asked with
Average ground projector distance between other interference unmanned plane base stations；It is all unmanned planes in addition to the k of unmanned plane base station
The same frequency power signal that base station is transmitted equally can be approximated to be the unmanned plane channel that N-1 possess same disturbance channel condition and pass
The same frequency power signal come；
The wherein function f in formula (1) are as follows:
Wherein, h represents the height of unmanned plane base station；It represents between user terminal and other interference unmanned plane base stations to be asked
Average ground projector distance；B and C represent constant；α represents channel path loss coefficient；η represents non line-of-sight communication fading channel
Coefficient；B, C, α, η are the parameter for calculating air to surface horizon communication channel probability model, and parameter B, C, α, η are determined by environment, are used to
The channel condition under different scenes is modeled, function f is used to find out the channel condition between unmanned plane base station and user.Therefore, first
It finds outBringing function f into can be obtained by the average interference channel being subject at the user of each unmanned plane base station.
The present invention models this intensive net by more member's mean field game frameworks under a continuous time state
Mutual interference environment under network, it is contemplated that super-intensive is tethered at the mutual interference problem in unmanned plane base station communication network, such a
Under intensive network, the mutual interference between a large amount of unmanned plane base station was considered originally, such that calculation amount is extremely big, led to
Building Mean-Field Model is crossed, for the typical unmanned plane base station in a network, a large amount of base stations are carried out its interference flat
Approximate, a base station need to only consider an average distracter, greatly reduce computation complexity.
Step 3: establishing cost function: using the speed on unmanned plane vertical direction as motion space, being believed according to communication link
It makes an uproar than constructing corresponding cost function with unmanned plane energy consumption, making one asks the smallest optimization of long run average cost function
Topic, according to certain weight ratio, acquires optimal joint Power and rate control, so that long run cost function obtains minimum value.
A large amount of aerial unmanned plane base stations that are tethered at are that terrestrial user provides data and passes service up and down, composition super-intensive network,
Each user can receive the common-channel interference that other base stations are transmitted, and be tethered at unmanned plane base station by aerial unmanned plane part and ground
It is formed for electric car, due to the presence of service cable, is tethered at the cruising ability of unmanned plane, the real-time of its control and accuracy and all compares
It is higher.Without loss of generality, for use some frequency range by unmanned plane base station service terrestrial user k, it can not only be received
The useful signal transmitted to the unmanned plane base station for serving it, while it is dry also to receive the same frequency that other base stations are transmitted in network
Disturb signal.The corresponding system equation of the mean field game framework of foundation, including system dynamical equation and relevant cost function, so that
Final gained scheme can effectively promote network performance.It is average that unmanned plane base station is tethered in the constructed super-intensive based on interference
In the betting model of field, communication quality and energy consumption are two parameters important in actual moving process.With unmanned plane base station k's
Signal to Interference plus Noise Ratio for user, in receiving end are as follows:
Wherein, λk(t) Signal to Interference plus Noise Ratio of unmanned plane base station k is represented；Pr,k,kFor the power of received useful signal；Iu,k(t)
Represent practical received interfering signal power；N0Represent noise；
The wherein P in formula (3)r,k,kFor,
Pr,k,k=PLoSPk|Xk,k|-α+PNLoSηPk|Xk,k|-α(4),
Wherein, PLoSAnd PNLoSRepresent communication channel whether be horizon communication probability；Xk,kIt is used for unmanned plane base station k with it
Linear distance between family；PkRepresent the transmission power of unmanned plane base station k；α represents channel path loss coefficient；η represents non line of sight
Communication channel attenuation coefficient；Xk,kRepresent the linear distance between the user of unmanned plane base station k and unmanned plane base station k.
In practice by average interference channel derived from step 2It brings (4) formula into, makes an uproar so that the letter of negative receiving end is dry
Than being for the first item of cost functionWhen first item minimum so that receiving
Hold Signal to Interference plus Noise Ratio bigger, communication quality is higher.
For Level Change of the unmanned plane base station within the control period, dynamical system needs additional energy consumption, additional consumption
Can and the actual height of unmanned plane base station be sized, herein quadratic component highly to regulate the speed related with the speed of adjustment
Metric as energy consumption.
In this mean field betting model, mean field item inscribes the member in a certain state in the overall situation when indicating a certain
Distribution:
Wherein, m (t, h) represents mean field item；K represents unmanned plane base station k；N represents unmanned plane base station number in network；h
Represent the height of unmanned plane base station.
Designed cost function should include mean field item, meet user communication quality simultaneously to meet purpose of design
Reduce unmanned plane base station height adjustment bring energy loss to the greatest extent, designed cost function includes the two, therefore, unmanned plane
The totle drilling cost function of base station k brings formula (1) and formula (4) into formula (3) by user communication quality and energy loss adduction gained
Obtain the totle drilling cost function of unmanned plane base station k:
Wherein, ck(t, h) represents the totle drilling cost function of unmanned plane base station k；ω1And ω2Weighted factor is represented, so that two
Cost function is in a dimension；Represent the average emitted power of the unmanned plane base station in addition to k interfered；m(t,h)
Represent mean field item；D represents differential operator；The second order term of representation speed, for measuring unmanned plane because height change is made
At additional energy consumption.
The present invention solves the problems, such as that technical solution used by above-mentioned minimum average cost function is as described below:
The continuous HJB equation that unmanned plane base station dynamical system is derived according to existing mature bellman theory, further according to existing
There is mean field theory to derive the FPK equation for stating mean field evolution under the scene.
Designed mean field betting model is regarded as between mean field composed by a certain member and other members
Differential game, independent variable space are time and state.In order to realize the convergence of game equilibrium, derive that the optimal dynamic of member is asked
Hamilton-Jacobi-Bellman (HJB) differential equation of solution are as follows:
Wherein,For partial differential operator,For the Chinese Mill in the HJB function
Pause function, and u (t, h) is cost function.
Thus it is derived from the Fokker-Planck- for solving mean field positive evolution with all member's current behaviors
Kolmogorov (FPK) differential equation are as follows:
Wherein,For partial differential operator.
It is proposed that a kind of algorithm iteration based on finite difference calculus solves the Simultaneous Equations of HJB and FPK.First continuous
Time and state variable domain carry out discretization, and discrete [0, T] is [0, tmaxΔ t], discrete step is away from for Δ t, status field [hmin,
hmax] discrete for [hminΔh,hmaxΔ h], discrete step is away from for Δ h.The continuous independent variable space of two dimension after discretization can be regarded as
One tmax×(hmax-hmin+ 1) matrix.The replacement of differential pair differential is carried out, using Upwind difference scheme herein with valence
For value function, Upwind difference scheme are as follows:
Wherein,For partial differential operator, U (t, h) is the cost function of discretization.
The algorithm of the solution simultaneous HJB and FPK equation group based on finite difference calculus proposed is as described below:
Firstly, solving the FPK equation of discretization according to Upwind difference scheme:
Wherein, M (t, h) is the average field matrix of discretization, and V (t, h-1) is the rate matrices of discretization,For partial differential
Operator.
The HJB equation for solving discretization acquires cost function:
Wherein, U (t, h) is the cost function matrix of discretization, C (V*(t, h), M (t, h)) be discretization cost letter
Number, V*(t, h) is current optimum control matrix.
According to the first order necessary condition of the Hamiltonian in HJB equation, acquired by following formula in Mean field instantly
Optimum control under evolution:
This iterative process is repeated with obtained optimum control, until reaching convergence precision requirement.The v finally obtained*I.e.
It is derived for the optimal height regulation scheme of unmanned plane base station by obtaining optimum control i.e. velocity vector from system equation
The optimal height regulation scheme of each unmanned plane, gained scheme are more rigorous.
The present invention shows all rows for being tethered at unmanned plane base station under different conditions in the control period by numerical result
It is characterized, acts not only as the scheme of practical operation, or other decisions make behavior prediction reference.
Embodiment:
The setting of design parameter value in diagram provided in following instance and model is primarily to illustrate this hair
Bright basic conception and simulating, verifying done to the present invention, in specific application environment, visual actual scene and demand are fitted
Work as adjustment.
A kind of subzone network includes 500 unmanned plane base stations, and each small base station is in each time slot by sharing a channel
Service user, each time slot user only connect with one of unmanned plane base station.Given elemental height is distributed as being uniformly distributed,
It is 0 that mean value is received in communicating link data transmission, the influence for the white Gaussian noise that variance is 1.
It is that the equilibrium state under being uniformly distributed is averaged field distribution that Fig. 2, which show all member conditions of the invention initial, first
When beginning is distributed as being uniformly distributed, the quantity in higher unmanned plane is being reduced, this illustrates the unmanned plane base station of high position rich
It is begun to decline after playing chess beginning, to reinforce the signal strength of own services user terminal, improves communication quality.
Fig. 3 show equilibrium state of the present invention and is averaged the sectional view of field distribution, specific 4 kinds of specific elemental heights nobody
The state changes in distribution of machine.It can be seen that the unmanned plane base station distribution probability in maximum height is vertical after the control period starts
Quarter is reduced to 0, this illustrates that all unmanned plane base stations in the height have all selected decline so that it is to being taken at the first moment
The communication quality of business user is able to maintain that in higher level.Distribution probability in 1020 meters of unmanned plane base stations is in control week
There is a rising by a small margin in phase in the end of term.Distribution probability in 1080 meters of unmanned plane base station remains stable first, then locates
In downward trend.It can be seen that 1020 meters and 1080 meters at unmanned plane base station distribution probability change curvature with the time by
It gradually reduces, this is because more and more unmanned plane base stations are in lower height as time goes by, this results in each
User, which receives place, will receive bigger interference signal.
It is to be uniformly distributed the optimal height control program of lower member that Fig. 4, which show initial all member conditions of the invention, respectively
The corresponding optimal control policy in unmanned plane base station of a state.It can be seen that, all unmanned plane base stations are all controlling in figure
Selection decline comes so that cost function is low as far as possible after period starts.And the speed of all unmanned plane base stations is all gradually becoming smaller,
This is because all unmanned plane base stations all have a declining tendency, will lead to bigger interference signal, in this case nobody
Machine base station similarly declines the influence played to cost function first item communication quality and will become smaller, therefore can select with compromising
Lower speed reduces cost function.
Fig. 5 show the present invention, and average Signal to Interference plus Noise Ratio level is at any time in obtained optimum control scheme lower network
Distribution, illustrates under obtained optimal height Adjusted Option, and the average communication quality of user is at any time in whole network
Situation of change can from figure as us are compared with the mobile scheme of static scheme and a kind of fixed rate as a control group
To see that the control program based on mean field game proposed possesses better communication performance, control is shown by numerical result
All behavioural characteristics for being tethered at unmanned plane base station under different conditions, act not only as the scheme of practical operation in period processed,
Or other decisions make behavior prediction reference.
Claims (4)
1. a kind of super-intensive based on interference is tethered at unmanned plane base station height adjusting method, which is characterized in that same for being in
The communication link of the multiple no-manned plane of frequency range establishes interference channel mean field betting model, based on group's state averagely come describe with
The dynamical equation of other members interaction, updates to obtain the optimum control of height adjustment speed by continuous iteration.
2. a kind of super-intensive based on interference according to claim 1 is tethered at unmanned plane base station height adjusting method, special
Sign is, follows the steps below to implement:
Step 1: building system model: system model is unmanned plane base station set, is usedIt indicates,
The same channel is shared simultaneously and carries out downlink data transmission in N number of unmanned plane base station；
Step 2: carrying out mean field approximation to interference channel: before the control period starts, setting the transmitting of all unmanned plane base stations
Power calculates the average channel of interference according to the interfering signal power that the serviced user's receiving terminal in unmanned plane base station receives；
Step 3: establishing cost function: using the speed on unmanned plane vertical direction as motion space, according to communication link signal-to-noise ratio
Corresponding cost function is constructed with unmanned plane energy consumption, making one makes the smallest optimization problem of long run average cost function,
According to certain weight ratio, optimal joint Power and rate control are acquired, so that long run cost function obtains minimum value.
3. a kind of super-intensive based on interference according to claim 2 is tethered at unmanned plane base station height adjusting method,
It is characterized in that, the specific method of mean field approximation is in the step 2:
Before the control period starts, set the transmission powers of all unmanned plane base stations asThe average channel of interference is are as follows:
Wherein, k represents unmanned plane base station k；U represents some channel that unmanned aerial vehicle group is used in conjunction with；Represent unmanned plane
The interfering signal power that k serviced user's receiving terminal in base station receives,It is all nobody in addition to the k of unmanned plane base station
The same frequency power signal that machine base station is transmitted；N represents unmanned plane base station number in intensive unmanned plane base station network；It represents and makes
At the average emitted power of the unmanned plane base station in addition to k of interference；hjRepresent the height of unmanned plane base station j；T represents the time；
Represent the average ground projector distance between user terminal and other interference unmanned plane base stations to be asked；
The wherein function f in formula (1) are as follows:
Wherein, h represents the height of unmanned plane base station；It represents flat between user terminal and other interference unmanned plane base stations to be asked
Equal floor projection distance；α represents channel path loss coefficient；η represents non line-of-sight communication channel fading coefficient；B and C represents normal
Number.
4. a kind of super-intensive based on interference according to claims 2 or 3 is tethered at unmanned plane base station height adjusting method,
It is characterized in that, establishing cost function in the step 3, detailed process is as follows,
Signal to Interference plus Noise Ratio by taking the user of unmanned plane base station k as an example, in receiving end are as follows:
Wherein, λk(t) Signal to Interference plus Noise Ratio of unmanned plane base station k is represented；Pr,k,kRepresent the power of received useful signal；Iu,k(t) generation
Table interfering signal power；N0Represent noise；
The wherein P in formula (3)r,k,kFor,
Pr,k,k=PLoSPk|Xk,k|-α+PNLoSηPk|Xk,k|-α, (4),
Wherein, PLoSAnd PNLoSRepresent communication channel whether be horizon communication probability；Xk,kRepresent unmanned plane base station k and its user
Between linear distance；PkRepresent the transmission power of unmanned plane base station k；α represents channel path loss coefficient；It is logical that η represents non line of sight
Believe channel fading coefficient；Xk,kRepresent the linear distance between the user of unmanned plane base station k and unmanned plane base station k.
The totle drilling cost function of unmanned plane base station k is by user communication quality and energy loss adduction gained, therefore by formula (1) and formula
(4) it brings formula (3) into and obtains the totle drilling cost function of unmanned plane base station k:
Wherein, ck(t, h) represents the totle drilling cost function of unmanned plane base station k；ω1And ω2Weighted factor is represented, so that two costs
Function is in a dimension；Represent the average emitted power of the unmanned plane base station in addition to k interfered；M (t, h) is represented
Mean field item；D represents differential operator；The second order term of representation speed, caused by measuring unmanned plane because of height change
Additional energy consumption.
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