CN117295097B - Unmanned aerial vehicle downlink robust speed splitting method for signal direction angle error - Google Patents

Unmanned aerial vehicle downlink robust speed splitting method for signal direction angle error Download PDF

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CN117295097B
CN117295097B CN202311586215.1A CN202311586215A CN117295097B CN 117295097 B CN117295097 B CN 117295097B CN 202311586215 A CN202311586215 A CN 202311586215A CN 117295097 B CN117295097 B CN 117295097B
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unmanned aerial
aerial vehicle
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downlink
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CN117295097A (en
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欧阳键
陈竹林
吴庆梓
毛益伟
林敏�
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Nanjing University of Posts and Telecommunications
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W24/00—Supervisory, monitoring or testing arrangements
    • H04W24/02—Arrangements for optimising operational condition
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B17/00—Monitoring; Testing
    • H04B17/30—Monitoring; Testing of propagation channels
    • H04B17/391—Modelling the propagation channel
    • 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
    • H04W16/24—Cell structures
    • H04W16/28—Cell structures using beam steering
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
    • H04W4/30—Services specially adapted for particular environments, situations or purposes
    • H04W4/40—Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P]

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  • Computer Networks & Wireless Communication (AREA)
  • Signal Processing (AREA)
  • Physics & Mathematics (AREA)
  • Electromagnetism (AREA)
  • Mobile Radio Communication Systems (AREA)

Abstract

The invention discloses a method for splitting a downlink robust rate of an unmanned aerial vehicle for signal direction angle errors, which aims at minimizing signal transmitting power to be an optimization target, and builds a robust beam forming optimization problem of a rotor unmanned aerial vehicle downlink RSMA communication system by taking public rate and private rate as constraint conditions, so that the service quality requirement of a user is fully considered; the signal beam forming gain approximation method based on the second-order Maclalin expansion is provided, so that the design difficulty of a downlink RSMA robust algorithm of the unmanned aerial vehicle communication system is effectively reduced; and a signal direction angle error robust beam forming algorithm combining the S-Procedure and the penalty function is designed based on the method, so that a new solution is provided for a robust beam forming technology considering unmanned aerial vehicle jitter. According to the unmanned aerial vehicle downlink robust rate splitting method for signal direction angle errors, the robust performance of an unmanned aerial vehicle communication system is effectively improved, and meanwhile the unmanned aerial vehicle air-ground communication service quality is improved.

Description

Unmanned aerial vehicle downlink robust speed splitting method for signal direction angle error
Technical Field
The invention relates to a method for splitting downlink robust speed of an unmanned aerial vehicle facing signal direction angle errors, and belongs to the technical field of unmanned aerial vehicle communication.
Background
The unmanned aerial vehicle is used as a communication node, and has the characteristics of high mobility, quick deployment, wide coverage range and the like. Meanwhile, the problems of battery life, signal interference, communication bandwidth, flight stability and the like exist. In a downstream communication system of an unmanned aerial vehicle where multiple users exist, interference is a problem which is difficult to ignore. Conventional interference management methods generally employ space division multiple access methods: the disturbance is completely regarded as noise. Non-orthogonal multiple access method>: the interference decoding is completely performed. />The positions of users need to be reasonably distributed in a limited space, and in many scenes, interference among antennas exists, so that the signal quality is reduced, and the positions of the users are +.>Complex signal processing and interference management techniques are required to ensure interference minimization, greatly increasing the complexity of the system, while improving spectral efficiency, and at the same time resulting in higher system power consumption.
Therefore, it is worth studying to perform efficient interference management to improve the spectral efficiency of the communication system while reducing the system power consumption.
In addition, due to the influences of atmospheric turbulence, shaking of the rotor unmanned aerial vehicle and other factors, an angle shaking error exists in the airborne antenna inevitably, so that a beam cannot be stably aligned to a target user, and the communication quality is obviously reduced. How to reduce the system power consumption and obtain better spectrum efficiency while guaranteeing the data transmission quality becomes the technical problem which needs to be solved in the current emergency.
Disclosure of Invention
The purpose is as follows: in order to overcome the defects in the prior art, the invention provides a method for separating the down robust velocity of an unmanned aerial vehicle facing signal direction angle errors, and the down robust velocity of the unmanned aerial vehicle is constructed aiming at the signal direction angle errors caused by body shake during the flight of the unmanned aerial vehicle with a rotor wingThe (rate splitting multiple access) communication system robust beamforming optimization problem provides an approximation method and designs a robust beamforming algorithm. The robustness of the unmanned aerial vehicle communication system is effectively improved, and meanwhile, the air-ground communication service quality of the unmanned aerial vehicle is improved.
The technical scheme is as follows: in order to solve the technical problems, the invention adopts the following technical scheme:
a method for separating downlink robust speed of unmanned aerial vehicle facing signal direction angle error comprises the following steps:
step 1: acquiring downlink based on linear array antennaAnd (5) transmitting the model.
Step 2: according to downlink based on linear array antennaTransmission model for obtaining down-going +.>The problem of robust beamforming optimization of a communication system.
Step 3: solving rotor unmanned aerial vehicle descendingThe problem of robust beamforming optimization of a communication system is to obtain beamforming vectors of public signals and private signals.
Preferably, the downlink based on the linear array antennaA transmission model, comprising: one is provided withUniform linear array unmanned aerial vehicle base station with multiple antennas and +.>The base station of the unmanned aerial vehicle transmits public signals to all ground users by adopting a protocol>And private signal->User->Received signal->The calculation formula is as follows:
；
wherein,the representation is presented to the useriPrivate signal sent,/->The representation is +.>The private signal to be transmitted is transmitted,and->，/>Respectively represent common signals->And private signal->Is a beam forming vector, ">Representing private signal->Is a beam forming vector, ">Representation ofNSpace of vector of dimension complex, ->Is additive white Gaussian noise +.>Representing a complex Gaussian distribution +.>Is noise power +.>Is unmanned plane and ground user->Air-ground link between->Is->Is a transpose of (a).
As a preferred embodiment of the present invention,the calculation formula is as follows:
；
wherein,，cfor the speed of light->Is carrier center frequency>For unmanned aerial vehicle to ground user->Distance between->And->Unmanned aerial vehicle and ground user respectivelymCoordinates of (c)，/>Is a linear array half-wavelength direction vector.
As a preferred embodiment of the present invention,the calculation formula is as follows:
；
wherein,is imaginary unit, ++>，/>For unmanned aerial vehicle basic station antenna quantity, < >>Is the signal direction angle.
As a preferred embodiment of the present invention,the calculation formula is as follows:
；
wherein,for unmanned aerial vehicle to ground user->Signal direction angle estimate of +.>As an upper bound for the angle jitter error,representing a 2-norm.
As a preferable scheme, the rotor unmanned aerial vehicle descendsThe robust wave beam forming optimization problem of the communication system is calculated as follows:
；
；
；
in the method, in the process of the invention,for punishment factors->，/>The rank of the matrix is represented and,；
wherein,for matrix->Feature vector corresponding to maximum feature value, < ->Is->Is>Is a public signal auxiliary variable, < >>Is a private signal auxiliary variable, < >>，/>，/>，/>，/>，/>Representing the second order Maclalin expansion approximation expression introduced value,>and->User +.>Reachable rate threshold for public and private signals, < +.>、/>。
Preferably, the method comprisesThe calculation formula is as follows:
=/>；
in the method, in the process of the invention,representation->Is the first of (2)kLine 1lModulo value of column element,/->；
Wherein,representing the exclusive OR operation, < >>，；
The saidThe calculation formula is as follows:
；
in the method, in the process of the invention,，；
wherein,representation->Is the first of (2)kLine 1lModulo value of column element,/->，/>Representing an imaginary part;
the saidThe calculation formula is as follows:
；
in the method, in the process of the invention,；
wherein,、/>、/>respectively indicate->Is the first of (2)kLine 1kColumn (th)kLine 1jColumn (th)kLine 1lModulo value of column element,/->，/>Representing the real part;
the saidThe calculation formula is as follows:
=/>；
in the method, in the process of the invention,representation->Is the first of (2)kLine 1lModulo value of column element,/->；
The saidThe calculation formula is as follows:
；
in the method, in the process of the invention,，；
wherein,representation->Is the first of (2)kLine 1lModulo value of column element,/->；
The saidThe calculation formula is as follows:
；
in the method, in the process of the invention,；
wherein,、/>、/>respectively indicate->Is the first of (2)kLine 1kColumn (th)kLine 1jColumn (th)kLine 1lModulo value of column element,/->。
Preferably, the step 3 specifically includes:
solving rotor unmanned aerial vehicle descending by matlab simulation softwareRobust beamforming optimization problem of communication system to obtain rank-one matrix +.>。
Preferably, the matlab simulation software adopts CVX convex optimization problem numerical calculation software.
The beneficial effects are that: according to the unmanned aerial vehicle downlink robust rate splitting method for signal direction angle errors, which is provided by the invention, the signal transmitting power is minimized as an optimization target, the robust beam forming optimization problem of a rotor unmanned aerial vehicle downlink RSMA communication system taking public rate and private rate as constraint conditions is constructed, and the service quality requirement of a user is fully considered; the signal beam forming gain approximation method based on the second-order Maclalin expansion is provided, so that the design difficulty of a downlink RSMA robust algorithm of the unmanned aerial vehicle communication system is effectively reduced; and a signal direction angle error robust beam forming algorithm combining the S-Procedure and the penalty function is designed based on the method, so that a new solution is provided for a robust beam forming technology considering unmanned aerial vehicle jitter.
Drawings
Fig. 1 is an algorithm flow chart of an unmanned aerial vehicle downlink robust rate splitting method facing signal direction angle errors.
Fig. 2 is a system model diagram of an unmanned aerial vehicle downlink robust rate splitting method facing signal direction angle errors.
Fig. 3 is a histogram of probability distribution of reachable rates of 1 public signals of a user under a method for splitting downlink robust rates of unmanned aerial vehicles facing signal direction angle errors.
Fig. 4 is a histogram of probability distribution of reachable rates of user 2 public signals under a method for splitting downlink robust rates of unmanned aerial vehicles facing signal direction angle errors.
Fig. 5 is a histogram of probability distribution of reachable rates of 3 public signals of a user under a method for splitting downlink robust rates of unmanned aerial vehicles facing signal direction angle errors.
Fig. 6 is a histogram of the probability distribution of the reachable rate of the private signal of the user 1 under the unmanned aerial vehicle downlink robust rate splitting method facing the signal direction angle error.
Fig. 7 is a histogram of probability distribution of the reachable rate of the private signal of the user 2 under the unmanned aerial vehicle downlink robust rate splitting method facing the signal direction angle error.
Fig. 8 is a histogram of probability distribution of the reachable rate of the private signal of the user 3 under the unmanned aerial vehicle downlink robust rate splitting method facing the signal direction angle error.
Fig. 9 is a graph showing the change of the total power of signal transmission along with the threshold value of the achievable rate of the user signal in the down robust rate splitting method of the unmanned aerial vehicle facing the signal direction angle error.
Detailed Description
The following description of the embodiments of the present invention will be made more apparent and fully by reference to the accompanying drawings, in which embodiments of the invention are shown, and in which it is evident that the embodiments shown are only some, but not all embodiments of the invention. All other embodiments, which can be made by a person skilled in the art without any inventive effort, are intended to be within the scope of the present invention.
The invention will be further described with reference to specific examples.
Referring to fig. 1, the invention provides a method for separating downlink robust velocity of an unmanned aerial vehicle facing signal direction angle errors, which is realized by the following steps:
step 1, establishing a downlink based on a linear array antenna aiming at signal direction angle errors caused by body shake during flight of a rotor unmanned aerial vehicleAnd (5) transmitting the model.
Step 2, constructing downlink based on linear array antennaIn the transmission model, the minimum signal transmitting power is used as an optimization target, and the reachable speed of a public signal and the reachable speed of a private signal are used as constraint conditions for the downstream +.>The problem of robust beamforming optimization of a communication system.
And step 3, providing a signal beam forming gain approximation method based on second-order Maclalin expansion, and converting the linear array angle error.
Step 4, design association-/>And solving a downstream ++of the rotor unmanned aerial vehicle by a signal direction angle error robust beam forming algorithm of a penalty function method>The problem of robust beamforming optimization of a communication system.
Further, in one embodiment, the downlink based on the linear array antenna in step 1The transmission model, as shown in fig. 2, includes: one is provided with->Uniform linear array unmanned aerial vehicle base station with multiple antennas and +.>The single antenna ground users. Unmanned aerial vehicle base station adopts->Protocol transmits a common signal to all ground subscribers +.>And private signal->，，/>The representation is presented to the useriPrivate signal sent,/->。
Public signalCan be decoded by all users, while the private signal +.>Can only be compromised by the user>Decoding, user->Received signal->Can be expressed as:
（1）
wherein,and->，/>Respectively represent common signals->And private signal->Is a beam forming vector, ">Representing private signal->Is a beam forming vector, ">Representation ofNThe complex vector space is maintained,is additive white Gaussian noise +.>Representing a complex Gaussian distribution +.>Is noise power +.>Is unmanned plane and ground user->Air-ground link between->Is->Transpose of->Can be expressed as:
（2）
wherein,，cfor the speed of light->Is carrier center frequency>For unmanned aerial vehicle to ground user->Distance between->And->Unmanned aerial vehicle and ground user respectivelymCoordinates of->Is a linear array half-wavelength direction vector, expressed as:
（3）
wherein,is imaginary unit, ++>，/>For unmanned aerial vehicle basic station antenna quantity, < >>Is the signal direction angle.
Considering that unmanned aerial vehicle is influenced by airflow and self vibration in flight process, unmanned aerial vehicle and userThere is an angle jitter error between the array antenna direction angles>Signal direction angle->Can be expressed as:
（4）
wherein,for unmanned aerial vehicle to ground user->Signal direction angle estimate of +.>As an upper bound for the angle jitter error,representing a 2-norm.
Further, the rotor unmanned aerial vehicle descendsThe problem of robust beamforming optimization of a communication system is specifically expressed as follows:
（5a）
(5b)
(5c)
wherein,and->User +.>The achievable rates of public and private signals, < >>And->User +.>The achievable rate threshold value for both public and private signals.
Order theAnd add +.>And->Rank one constraint, optimization problem->Can be equivalently expressed as:
(6a)
(6b)
(6c)
(6d)
(6e)
wherein,representing the rank of the matrix, +.>Representing the maximum order of the sub-type of the matrix that is not zero.
Further, in one embodiment, the approximation method proposed in step 3 specifically operates as follows:
first, beamforming gainCan be equivalently expressed as:
(7)
wherein,for beamforming vector +.>Is->Is the first of (2)kLine 1kModulo value of column element,/->Is the first of (2)kLine 1lModulo value of column element,/->Is the first of (2)kLine 1lThe angle information of the column elements,，/>。
second, gain for beamformingPerforming second-order Maclalin expansion:
(8)
wherein,，，/>，/>。
next, use is made of，/>Deducing beam forming gain->Is a second order majulin expansion approximation expression:
(9)
wherein,，/>，/>=/> ，/>，/>,。
further, the method comprises the steps of,=/>，/>，/>=/>，/>，，/>。
wherein,representation->Is the first of (2)kLine 1lModulo value of column element,/->。
，/>。/>Representation->Is the first of (2)kLine 1lModulo value of column element,/->，/>Representing the imaginary part. />Representation->Is the first of (2)kLine 1lModulo value of column element,/->。。/>Representation->Is the first of (2)kLine 1lThe modulus value of the column of elements,。/>representing the exclusive OR operation, < >>，。/>。/>、、/>Respectively indicate->Is the first of (2)kLine 1kColumn (th)kLine 1jColumn (th)kLine 1lThe modulus value of the column of elements,，/>representing the real part. />。/>、/>、/>Respectively indicate->Is the first of (2)kLine 1kColumn (th)kLine 1jColumn (th)kLine 1lModulo value of column element,/->。
Finally, according to the approximate expression, the constraints (6 b), (6 c) can be expressed as:
（10a）
(10b)
further, in one embodiment, the specific operation of step 4 is as follows:
for the following：
(11)
For constraint (10 a):
2 (12)
thus, there is the following relationship:
+2/> (13)
according to the S-Procedure theorem, the above-mentioned conditions exist as follows:
such that:
(14a)
in the same way, the processing method comprises the steps of,such that:
(14b)
wherein,and->As auxiliary variables, (14 a) and (14 b) are in the form of Linear Matrix Inequalities (LMIs) of constraints (10 a) (10 b), respectively.
To solve the non-convex constraint (6 d) (6 e), a penalty function is introduced. Based on factsThe rank one constraint can be replaced by a penalty function with penalty factors, furthermore, < ->As a non-convex function, it is subjected to a first order taylor expansion:
(15)
wherein,for matrix->And the feature vector corresponding to the maximum feature value.
Finally, optimization problemCan be converted into convex optimization problems:
(16a)
(14a)(14b) (16b)
wherein,for punishment factors->。
The problem can be solved by adopting numerical calculation software of CVX convex optimization problemTo rank one matrix。
In order to verify the effect of the method of the invention, the examples of the invention give the following experiments:
as shown in fig. 3 to 8, in which，/>I.e. there are three users on the ground, the corresponding signal direction angle estimates are 36 +.>，168/>，135/>. Angle jitter error upper bound->. Public signal reachable rate threshold ++>1bps/Hz, private signal achievable rate threshold +.>3bps/Hz. As can be seen from the figure, the histograms of the robust schemes of the user 1, the user 2 and the user 3 are all positioned on the right side of the corresponding signal reachable rate threshold, namely the constraint condition of the signal reachable rate threshold can be well met by the user 1, the user 2 and the user 3, but the constraint condition cannot be met by the non-robust scheme, so that the robust scheme provided by the invention can effectively ensure the service quality of the user.
As shown in FIG. 9, wherein，/>I.e. there are three users on the ground, the corresponding signal direction angle estimates are +.>. Angle jitter error upper bound->And->. The threshold value range of the signal reachable rate is +.>. As shown, as the signal achievable rate threshold increases, the total power of the signal transmission increases. Meanwhile, the total transmission power required by the non-robust scheme is smaller than that of the robust scheme, which means that the cost of high tolerance of the robust scheme is more transmission power. The transmission total power required by the robust scheme with the angle jitter error of 4 degrees is larger than that of the robust scheme with the angle jitter error of 2 degrees, and the cost gradually becomes larger along with the increase of the uncertainty of the channel state information. But it can be seen that the cost of the robust scheme proposed in the present invention is quite modest.
The foregoing is only a preferred embodiment of the invention, it being noted that: it will be apparent to those skilled in the art that various modifications and adaptations can be made without departing from the principles of the present invention, and such modifications and adaptations are intended to be comprehended within the scope of the invention.

Claims (3)

1. A signal direction angle error-oriented unmanned aerial vehicle downlink robust speed splitting method is characterized by comprising the following steps of: the method comprises the following steps:
step 1: acquiring a downlink RSMA transmission model based on a linear array antenna;
step 2: acquiring a robust wave beam forming optimization problem of a rotor unmanned aerial vehicle downlink RSMA communication system according to a downlink RSMA transmission model based on a linear array antenna;
step 3: solving a robust beamforming optimization problem of a rotor unmanned aerial vehicle downlink RSMA communication system, and obtaining beamforming vectors of public signals and private signals;
the downlink RSMA transmission model based on the linear array antenna comprises the following steps: a uniform linear array unmanned aerial vehicle base station equipped with N antennas and M single-antenna ground users, the unmanned aerial vehicle base station transmitting a common signal s to all ground users using a protocol c And private signal s p Signal y received by user m m The calculation formula is as follows:
wherein s is p，i Representing the private signal sent to user i, s p，m Representing the private signal sent to user m,and->Respectively represent public signals s c And private signal s p，m Is a beamforming vector, w i Representing private signal s p，i Is a beam forming vector, ">Representing an N-dimensional complex vector space,/->Is additive white Gaussian noise +.>Representing a complex Gaussian distribution +.>Is the noise power, b m Is free ofAir-ground link between man-machine and ground user m, < >>Is h m Is a transpose of (2);
h m the calculation formula is as follows:
wherein,c is the speed of light, f c Is the carrier center frequency, d m ＝||q u -q m || 2 For the distance between the unmanned aerial vehicle and the ground user m, q u And q m Coordinates of unmanned plane and ground user m, respectively, < >>A half-wavelength direction vector for a linear array;
a m the calculation formula is as follows:
wherein j is an imaginary unit, N is more than or equal to 1 and less than or equal to N, N is the number of base station antennas of the unmanned aerial vehicle, and theta m Is the signal direction angle; θ m The calculation formula is as follows:
||Δθ m || 2 ≤ε m ；
wherein,for the estimated value epsilon of the signal direction angle from the unmanned aerial vehicle to the ground user m m Is the upper bound of the angle jitter error, I.I.I 2 Representing a 2-norm;
the robust wave beam forming optimization problem of the rotor unmanned aerial vehicle downlink RSMA communication system is calculated according to the following formula:
wherein, mu is penalty factor,is->tr (·) represents the rank of the matrix,
wherein,for matrix->Maximum characteristic value of>For matrix->Feature vector corresponding to maximum feature value, < ->Is W i Delta of the first order matrix of (a) c，m As an auxiliary variable of public signal delta p，m R is a private signal auxiliary variable c，m ，q c，m ，p c，m ，r p，m ，q p，m ，p p，m Representing the second order Maclalin expansion approximation expression introduced value,>and->The achievable rate threshold values for the user m public and private signals respectively,
the r is c，m The calculation formula is as follows:
r c，m ＝∑ k，l [Z c，m ] k，l ；
in [ z ] c，m ] k，l Representing z c，m The modulus value of the kth row and the first column element of (c),
wherein, the symbol "" -indicates a nor operation,
the q is c，m The calculation formula is as follows:
in the method, in the process of the invention,
wherein,representation B c，m Modulus value of the kth row and the first column element, B c，m ＝Im(Z c，m ) IM () represents the imaginary part;
the p is c，m The calculation formula is as follows:
in the method, in the process of the invention,
wherein,respectively represent A c，m The modulus value of the kth column, the kth row and the kth column element, A c，m ＝Re(Z c，m ) Re () represents the real part;
the r is p，m The calculation formula is as follows:
r p，m ＝∑ k，l [z p，m ] k，l ；
in [ z ] p，m ] k，l Representing Z p，m The modulus value of the kth row and the first column element of (c),
the q is p，m The calculation formula is as follows:
in the method, in the process of the invention,
wherein,representation B p，m Modulus value of the kth row and the first column element, B p，m ＝Im(Z p，m )；
The p is p，m The calculation formula is as follows:
in the method, in the process of the invention,
wherein,respectively represent A p，m The modulus value of the kth column, the kth row and the kth column element, A p，m ＝Re(Z p，m )。
2. The method for splitting the downlink robust rate of the unmanned aerial vehicle facing the signal direction angle error according to claim 1, wherein the method comprises the following steps: the step 3 specifically includes:
solving robust beamforming optimization problem of rotor unmanned aerial vehicle downlink RSMA communication system by adopting matlab simulation software to obtain rank-one matrix W c 、W m 。
3. The method for splitting the downlink robust rate of the unmanned aerial vehicle facing the signal direction angle error according to claim 2, wherein the method is characterized by comprising the following steps of: and the matlab simulation software adopts CVX convex optimization problem numerical calculation software.
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Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113207106A (en) * 2021-04-01 2021-08-03 北京邮电大学 Unmanned aerial vehicle fusion control method and device
CN116455439A (en) * 2023-06-15 2023-07-18 南京邮电大学 Unmanned aerial vehicle communication robust beam forming method based on second-order angle error approximation
CN116846435A (en) * 2023-06-30 2023-10-03 北京交通大学 Method for realizing rate splitting multiple access of mobile de-cellular large-scale MIMO system

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113207106A (en) * 2021-04-01 2021-08-03 北京邮电大学 Unmanned aerial vehicle fusion control method and device
CN116455439A (en) * 2023-06-15 2023-07-18 南京邮电大学 Unmanned aerial vehicle communication robust beam forming method based on second-order angle error approximation
CN116846435A (en) * 2023-06-30 2023-10-03 北京交通大学 Method for realizing rate splitting multiple access of mobile de-cellular large-scale MIMO system

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