CN115765899A

CN115765899A - Unmanned aerial vehicle communication beam domain channel simulation method and device, electronic equipment and medium

Info

Publication number: CN115765899A
Application number: CN202211027439.4A
Authority: CN
Inventors: 常恒泰; 王承祥; 黄杰; 黄晨; 冯瑞; 辛立建
Original assignee: Network Communication and Security Zijinshan Laboratory
Current assignee: Network Communication and Security Zijinshan Laboratory
Priority date: 2022-08-25
Filing date: 2022-08-25
Publication date: 2023-03-07

Abstract

The invention provides a method, a device, electronic equipment and a medium for simulating an unmanned aerial vehicle communication beam domain channel, wherein the method comprises the following steps: constructing an unmanned aerial vehicle communication channel scene model, wherein the model comprises scattering cluster parameters; aiming at a large-scale MIMO unmanned aerial vehicle channel, constructing a channel response matrix of a transmitting and receiving end array domain; based on a wave beam domain conversion matrix, converting a channel response matrix of the receiving and transmitting end array domain into a first channel response matrix of the receiving and transmitting end wave beam domain, and approximating a preset function in the first channel response matrix of the receiving and transmitting end wave beam domain to an impulse function to obtain a second channel response matrix of the receiving and transmitting end wave beam domain; and updating the scattering cluster parameters at each simulation time, and calculating the channel response of the nonzero channel element in the wave beam domain of the transceiving end at the current simulation time based on the second channel response matrix of the wave beam domain of the transceiving end until a preset simulation time length is reached. The invention can obviously reduce the complexity of the beam domain channel simulation of the large-scale MIMO unmanned aerial vehicle.

Description

Unmanned aerial vehicle communication beam domain channel simulation method and device, electronic equipment and medium

Technical Field

The invention relates to the technical field of communication, in particular to a method and a device for simulating a communication beam domain channel of an unmanned aerial vehicle, electronic equipment and a medium.

Background

Unmanned aerial vehicle communication is a key enabling technology and an important application scene of a sixth generation (6G) mobile communication system, the coverage range of a future wireless communication network can be further expanded, and the spectrum efficiency and the system capacity of the existing communication system can be remarkably improved by combining large-scale Multiple-Input Multiple-Output (MIMO) system configuration.

At present, the unmanned aerial vehicle channel model mainly includes: ray-Tracing Channel models (RT), correlation-Based Stochastic Channel models (CBSM), and Geometry-Based Stochastic Channel models (GBSM). Compared with the CBSM scheme, the GBSM scheme has more definite physical significance, can avoid the defects that the RT scheme is high in complexity and only suitable for a characteristic scene, and has strong expandability, so that the GBSM is widely applied to a large number of unmanned aerial vehicle channel models.

However, when the GBSM is applied to modeling of a large-scale MIMO channel for unmanned aerial vehicle communication, since the channel responses of different sub-channels are separately simulated and calculated in the channel simulation process, the complexity of the channel simulation is greatly increased along with the great increase of the number of the sub-channels.

Disclosure of Invention

The invention provides a method, a device, electronic equipment and a medium for simulating a beam domain channel of unmanned aerial vehicle communication, which are used for solving the defect that the complexity of channel simulation is greatly increased along with the great increase of the number of sub-channels because the channel responses of different sub-channels are respectively simulated and calculated in the channel simulation process when GBSM is applied to the modeling of the large-scale MIMO channel of unmanned aerial vehicle communication in the prior art, and the aim of remarkably reducing the complexity of the beam domain channel simulation of the large-scale MIMO unmanned aerial vehicle is fulfilled.

The invention provides an unmanned aerial vehicle communication beam domain channel simulation method, which comprises the following steps:

constructing an unmanned aerial vehicle communication channel scene model, wherein the unmanned aerial vehicle communication channel scene model comprises scattering cluster parameters;

aiming at a large-scale multi-input multi-output MIMO unmanned aerial vehicle channel, constructing a channel response matrix of a receiving and transmitting end array domain;

based on a wave beam domain conversion matrix, converting the channel response matrix of the receiving and transmitting end array domain into a first channel response matrix of the receiving and transmitting end wave beam domain, and approximating a preset function in the first channel response matrix of the receiving and transmitting end wave beam domain to an impulse function to obtain a second channel response matrix of the receiving and transmitting end wave beam domain;

and updating the scattering cluster parameters at each simulation moment, and calculating the channel response of the nonzero channel elements at the current simulation moment in the wave beam domain of the transmitting and receiving ends based on the second channel response matrix of the wave beam domain of the transmitting and receiving ends until the preset simulation duration is reached.

According to the unmanned aerial vehicle communication wave beam domain channel simulation method provided by the invention, aiming at a large-scale multi-input multi-output MIMO unmanned aerial vehicle channel, a channel response matrix of a transceiving end array domain is constructed, and the method comprises the following steps:

dividing a large-scale MIMO unmanned aerial vehicle channel multipath scattering cluster into a far-field scattering cluster and a near-field scattering cluster;

constructing a far-field channel response matrix of a receiving and transmitting end array domain based on a guide vector structure under a plane wave stationary condition;

constructing a near-field channel response matrix of a receiving and transmitting end array domain based on a guide vector structure under a spherical wave nonstationary condition;

and superposing the far-field channel response matrix and the near-field channel response matrix of the transceiving end array domain to obtain the channel response matrix of the transceiving end array domain.

According to the method for simulating the communication beam domain channel of the unmanned aerial vehicle, provided by the invention, the large-scale MIMO unmanned aerial vehicle channel multipath scattering cluster is divided into a far-field scattering cluster and a near-field scattering cluster, and the method comprises the following steps:

under the condition that a uniform area array is configured at the ground end and a large-scale uniform area array is configured at the unmanned aerial vehicle end, dividing the large-scale MIMO unmanned aerial vehicle channel multipath scattering cluster into a far-field scattering cluster and a near-field scattering cluster according to the position of the scattering cluster.

According to the unmanned aerial vehicle communication beam domain channel simulation method provided by the invention, the far-field channel response matrix of the receiving and transmitting end array domain is constructed based on the guide vector structure under the stable condition of plane waves, and the method comprises the following steps:

constructing a far-field channel response matrix of a receiving and transmitting end array domain based on array response matrixes corresponding to all sub-arrays of a transmitting end under a far-field condition; wherein the guide vector structure under the plane wave stationary condition comprises: and the array response matrixes respectively correspond to the sub-arrays of the transmitting terminal under the far-field condition.

According to the unmanned aerial vehicle communication beam domain channel simulation method provided by the invention, the near-field channel response matrix of the receiving and transmitting end array domain is constructed based on the guide vector structure under the spherical wave non-stationary condition, and the method comprises the following steps:

constructing a near-field channel response matrix of a transceiving end array domain based on array response matrixes corresponding to all sub-arrays of a transmitting end under a near-field condition; wherein, the guiding vector structure under the non-stationary condition of the spherical wave comprises: the array response matrix corresponding to each sub-array of the transmitting terminal under the near field condition comprises a life and death factor corresponding to each sub-array of the transmitting terminal under the near field condition.

According to the method for simulating the communication wave beam domain channel of the unmanned aerial vehicle, the wave beam domain switching matrix comprises the following steps: a wave beam domain conversion matrix of a receiving end and a wave beam domain conversion matrix of a transmitting end;

the method further comprises the following steps:

determining a kronecker product of a beam domain conversion matrix of a receiving end in a pitching direction and a beam domain conversion matrix of the receiving end in a horizontal direction as the beam domain conversion matrix of the receiving end;

determining a kronecker product of a beam domain conversion matrix of the transmitting terminal array in a pitching direction and a beam domain conversion matrix in a horizontal direction as a beam domain conversion matrix of the transmitting terminal array for each transmitting terminal array;

and determining a block diagonal matrix composed of the beam domain switching matrices of different transmitting terminal arrays as the beam domain switching matrix of the transmitting terminal.

According to the method for simulating the communication wave beam domain channel of the unmanned aerial vehicle, the channel response matrix of the receiving and transmitting end array domain is converted into the first channel response matrix of the receiving and transmitting end wave beam domain based on the wave beam domain conversion matrix, and the method comprises the following steps:

and multiplying the beam domain switching matrix of the receiving end, the channel response matrix of the array domain of the transmitting and receiving ends and the beam domain switching matrix of the transmitting end in sequence to obtain a first channel response matrix of the beam domain of the transmitting and receiving ends.

According to the simulation method of the unmanned aerial vehicle communication beam domain channel provided by the invention, the updating of the scattering cluster parameters at each simulation moment comprises the following steps:

generating an attitude angle of the unmanned aerial vehicle at each simulation moment; wherein, unmanned aerial vehicle attitude angle includes: pitch angle, yaw angle, and roll angle;

constructing a coordinate rotation matrix based on the attitude angle of the unmanned aerial vehicle;

calculating scattering cluster parameters under a local coordinate system based on the coordinate rotation matrix;

and updating the scattering cluster parameters in the local coordinate system.

The invention also provides an unmanned aerial vehicle communication beam domain channel simulation device, which comprises:

the model building module is used for building an unmanned aerial vehicle communication channel scene model, and the unmanned aerial vehicle communication channel scene model comprises scattering cluster parameters;

the matrix construction module is used for constructing a channel response matrix of a transmitting and receiving end array domain aiming at a large-scale multi-input multi-output MIMO unmanned aerial vehicle channel;

a matrix conversion module, configured to convert a channel response matrix of the transceiving end array domain into a first channel response matrix of the transceiving end beam domain based on a beam domain conversion matrix, and approximate a preset function in the first channel response matrix of the transceiving end beam domain to an impulse function, so as to obtain a second channel response matrix of the transceiving end beam domain;

and the channel simulation module is used for updating the scattering cluster parameters at each simulation moment, and calculating the channel response of the nonzero channel element at the current simulation moment in the beam domain of the transceiving end based on the second channel response matrix of the beam domain of the transceiving end until the preset simulation time length is reached.

The invention further provides an electronic device, which includes a memory, a processor and a computer program stored in the memory and executable on the processor, and when the processor executes the program, the method for simulating the communication beam domain channel of the drone according to any one of the above methods is implemented.

The present invention also provides a non-transitory computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements a drone communication beam domain channel simulation method as any one of the above.

The invention also provides a computer program product comprising a computer program which, when executed by a processor, implements the drone communication beam domain channel simulation method as described in any one of the above.

The invention provides a method, a device, electronic equipment and a medium for simulating an unmanned aerial vehicle communication beam domain channel.A scene model of the unmanned aerial vehicle communication channel is established, wherein the scene model comprises scattering cluster parameters; then, aiming at a large-scale MIMO unmanned aerial vehicle channel, constructing a channel response matrix of a transmitting and receiving end array domain; based on the beam domain conversion matrix, converting the channel response matrix of the receiving and transmitting end array domain into a first channel response matrix of the receiving and transmitting end beam domain, and approximating a preset function in the first channel response matrix of the receiving and transmitting end beam domain as an impulse function to obtain a second channel response matrix of the receiving and transmitting end beam domain, namely, under the condition of approximation of the impulse function, modeling can be carried out on sparsity of a beam domain channel of the large-scale MIMO unmanned aerial vehicle; and finally, updating scattering cluster parameters at each simulation moment, and calculating the channel response of the nonzero channel elements in the beam domain of the transmitting and receiving ends at the current simulation moment based on the second channel response matrix of the beam domain of the transmitting and receiving ends until the preset simulation duration is reached.

Drawings

In order to more clearly illustrate the technical solutions of the present invention or the prior art, the drawings needed for the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and those skilled in the art can also obtain other drawings according to the drawings without creative efforts.

Fig. 1 is a schematic flow chart of a method for simulating a communication beam domain channel of an unmanned aerial vehicle according to the present invention;

fig. 2 is a schematic diagram of a communication scenario of an unmanned aerial vehicle provided by the present invention;

FIG. 3 is a schematic diagram of sub-array partitioning and scattering cluster partitioning provided by the present invention;

FIG. 4a is a schematic diagram of the channel response amplitude of the beam domain in an 8 × 8 uniform area array configuration provided by the present invention;

FIG. 4b is a diagram of the channel response amplitude of the beam domain in a 32 × 32 uniform area array configuration provided by the present invention;

FIG. 4c is a diagram of the channel response amplitude in the beam domain under a 64 × 64 uniform area array configuration provided by the present invention;

FIG. 5a is a schematic diagram of the simulation complexity of the BDCM model and the equivalent GBSM model provided by the present invention;

FIG. 5b is a schematic diagram of the channel capacity of the BDCM model and the equivalent GBSM model provided by the present invention;

FIG. 6a is a schematic diagram of the time autocorrelation function of the BDCM model and the equivalent GBSM model provided by the present invention;

FIG. 6b is a schematic diagram of the Doppler spread of the BDCM model and the equivalent GBSM model provided by the present invention;

fig. 7 is a schematic structural diagram of an unmanned aerial vehicle communication beam domain channel simulation apparatus provided in the present invention;

fig. 8 is a schematic structural diagram of an electronic device provided in the present invention.

Detailed Description

In order to make the objects, technical solutions and advantages of the present invention more apparent, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings, and it is obvious that the described embodiments are some, but not all embodiments of the present invention. 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 method for simulating the communication beam domain channel of the unmanned aerial vehicle is described in the following with reference to fig. 1 to 6.

Referring to fig. 1, fig. 1 is a schematic flow chart of a method for simulating a communication beam domain channel of an unmanned aerial vehicle according to the present invention. As shown in fig. 1, the method for simulating the beam domain channel of the unmanned aerial vehicle communication provided by the present invention may include the following steps:

101, constructing an unmanned aerial vehicle communication channel scene model, wherein the unmanned aerial vehicle communication channel scene model comprises scattering cluster parameters;

102, constructing a channel response matrix of a transmitting and receiving end array domain aiming at a large-scale MIMO unmanned aerial vehicle channel;

step 103, converting the channel response matrix of the receiving and transmitting end array domain into a first channel response matrix of the receiving and transmitting end beam domain based on the beam domain conversion matrix, and approximating a preset function in the first channel response matrix of the receiving and transmitting end beam domain to an impulse function to obtain a second channel response matrix of the receiving and transmitting end beam domain;

and step 104, updating the scattering cluster parameters at each simulation time, and calculating the channel response of the nonzero channel element in the wave beam domain of the transmitting and receiving end at the current simulation time based on a second channel response matrix of the wave beam domain of the transmitting and receiving end until a preset simulation time length is reached.

In step 101, a schematic view of a communication scenario of the drone is shown in fig. 1, and a model of a communication channel scenario of the drone is constructed based on the communication scenario of the drone.

Specifically, step 101 may comprise the following sub-steps:

step 1011, setting scene parameters of the unmanned aerial vehicle communication scene;

step 1012, generating scatterer parameters;

and step 1013, initializing channel simulation parameters.

In step 1011, the scene parameters of the drone communication scene include: scene range, scene type, antenna array configuration parameters of the transmitting and receiving end and coordinate sampling parameters of equal time intervals of the track of the transmitting and receiving end under the global coordinate. The configuration parameters of the antenna array at the transmitting and receiving end comprise: number of antenna units M of transmitting terminal (unmanned aerial vehicle) _T Number M of antenna units at receiving end (ground end) _R The number of units per line of the transmitting terminal antenna array is P _h The number of the elements in each row of the transmitting terminal antenna array is P _v The number Q of the units in each row of the receiving end antenna array _h And the number Q of units per column of the receiving end antenna array _v . The equal time interval coordinate sampling parameters of the receiving and transmitting end track under the global coordinate comprise: coordinates of transmitting end under global coordinates

And the coordinates of the receiving end in global coordinates

t is the different coordinate sampling instant.

In step 1012, the departure angle and arrival angle of the scatterer of the first hop and the last hop are generated based on the truncated gaussian distribution, and the scattering cluster propagation distances of the first hop and the last hop, that is, the scatterer parameters are generated based on the exponential distribution.

In particular, with t ₀ The parameter calculation of the mth sub-diameter in the nth scattering cluster at the moment is as follows:

by passing

Generating a horizontal angle component of the m-th sub-diameter exit angle in the n-th scattering cluster

Wherein, the first and the second end of the pipe are connected with each other,

represents the mean of the horizontal angular components of the departure angle,

represents the horizontal angular component variance of the departure angle.

By passing

Generating a vertical angle component of the mth sub-diameter exit angle in the nth scattering cluster

Wherein the content of the first and second substances,

the mean of the vertical angle components representing the angle of departure,

represents the variance of the vertical angle component of the departure angle.

By passing

Generating a horizontal angle component of the m-th sub-path arrival angle in the n-th scattering cluster

Wherein the content of the first and second substances,

the mean of the horizontal angle components representing the angle of arrival,

the horizontal angle component variance representing the angle of arrival.

By passing

Generating a vertical angle component of the m-th sub-path arrival angle in the n-th scattering cluster

the mean of the vertical angle components representing the angle of arrival,

the vertical angle component variance representing the angle of arrival.

By passing

Generating the first jump propagation distance of the mth sub-path in the nth scattering cluster

Wherein d is ^T Representing the expected value of the first hop propagation distance.

By passing

Generating the last hop propagation distance of the mth sub-path in the nth scattering cluster

Wherein d is ^R Representing the expected value of the last hop propagation distance.

Calculating the position of the central point of the first jump of the mth sub-path in the nth scattering cluster in the global coordinates by the expression (1):

represents t ₀ The position of the central point of the first jump of the mth sub-path in the nth scattering cluster in the time global coordinate,

represents t ₀ And coordinates of the transmitting end under the global time coordinates.

Calculating the position of the central point of the last jump of the mth sub-path in the nth scattering cluster in the global coordinates by the expression (2):

represents t ₀ The position of the central point of the last jump of the mth sub-path in the nth scattering cluster in the time global coordinate,

denotes t ₀ And the coordinates of the receiving end under the global time coordinates.

In step 1013, the channel simulation parameters in the initial state include: each scattering cluster is at t ₀ Time delay, multipath power and initial phase phi of time _n,m ～U[0,2π]。

In particular, by

Calculating the m-th minor diameter in the n-th scattering cluster at t ₀ Time delay tau of a moment _n,m (t ₀ ) Wherein, in the step (A),

the virtual time delay of the mth sub-path in the nth scattering cluster is expressed, the mth sub-path is subject to exponential distribution, c represents the speed of light,

by passing

Calculating the m-th minor diameter in the n-th scattering cluster at t ₀ Power P of time _n,m (t ₀ ) Wherein r is _τ Scaling factor, σ, representing the time delay _τ A spreading factor, Y, representing the time delay _n Represents the scattering cluster shadow fading factor, and follows normal distribution.

In addition, because in the large-scale MIMO configuration, the scattering cluster parameters may vary on the array axis, and a quenching phenomenon occurs, and the near-field scattering clusters are only visible to a part of the array units, as shown in fig. 3, in this embodiment, the large-scale array is divided into L · K sub-arrays according to K rows and L columns, and (L, K) is used to represent the sub-array in the kth row and the L column.

In step 102, a channel response matrix of a transmit-receive end array domain of a massive MIMO drone channel is constructed.

In step 103, the channel response matrix of the transceiving end array domain is converted into the first channel response matrix of the transceiving end beam domain by the beam domain conversion matrix. The method can be applied to transmission technologies such as beam forming and the like due to the conversion from the array domain to the beam domain, does not need additional beam forming processing and has resolvability.

The predetermined function in the first channel response matrix of the transceiving end beam field may be referred to as an f-function, which may be defined as

When a large-scale antenna array is configured with a sufficient number of antenna elements, the f-function can be approximated as an impulse function according to the law of lobada, i.e., the f-function is approximated as an impulse function

Under the approximate condition of impulse function, each scatterer only generates response on the wave beam with the closest value, and the sparsity of a second channel response matrix of the wave beam domain of the transmitting and receiving end is generated. That is, under the condition of impulse function approximation, the sparsity of the beam domain channel of the massive MIMO unmanned aerial vehicle can be modeled.

In step 104, because of the large-scale MIMO configuration, the scattering cluster parameters will change on the array axis, generating a fire phenomenon, updating the scattering cluster parameters (e.g., delay, power, phase, etc.) based on the time-varying trajectories of the transmitting end and the receiving end at each simulation time, and calculating the channel response of the non-zero channel elements in the beam domain of the transmitting end and the receiving end at the current simulation time through the second channel response matrix of the beam domain of the transmitting end and the receiving end until a preset simulation duration is reached. That is, because the large-scale MIMO unmanned aerial vehicle beam domain channel has the characteristic of sparsity, each channel element does not need to be calculated, only non-zero channel elements need to be simulated, and the complexity of the large-scale MIMO unmanned aerial vehicle beam domain channel simulation can be remarkably reduced.

In this embodiment, first, an unmanned aerial vehicle communication channel scene model is constructed, where the model includes scattering cluster parameters; then, aiming at a large-scale MIMO unmanned aerial vehicle channel, constructing a channel response matrix of a transmitting and receiving end array domain; based on the beam domain conversion matrix, converting the channel response matrix of the receiving and transmitting end array domain into a first channel response matrix of the receiving and transmitting end beam domain, and approximating a preset function in the first channel response matrix of the receiving and transmitting end beam domain as an impulse function to obtain a second channel response matrix of the receiving and transmitting end beam domain, namely, under the condition of approximation of the impulse function, modeling can be carried out on sparsity of a beam domain channel of the large-scale MIMO unmanned aerial vehicle; and finally, updating scattering cluster parameters at each simulation moment, and calculating the channel response of the nonzero channel elements in the beam domain of the transmitting and receiving ends at the current simulation moment based on the second channel response matrix of the beam domain of the transmitting and receiving ends until the preset simulation duration is reached.

Optionally, the step 102 includes the following sub-steps:

step 1021, dividing the large-scale MIMO unmanned aerial vehicle channel multipath scattering cluster into a far-field scattering cluster and a near-field scattering cluster;

step 1022, constructing a far-field channel response matrix of the transceiving end array domain based on the guide vector structure under the plane wave stationary condition;

step 1023, constructing a near-field channel response matrix of a transceiving end array domain based on a guide vector structure under the non-stationary condition of spherical waves;

and step 1024, superposing the far-field channel response matrix and the near-field channel response matrix of the transceiving end array domain to obtain a channel response matrix of the transceiving end array domain.

In step 1021, optionally, under the condition that a uniform area array is configured at the ground end and a large-scale uniform area array is configured at the unmanned aerial vehicle end, dividing the large-scale MIMO unmanned aerial vehicle channel multipath scattering cluster into a far-field scattering cluster and a near-field scattering cluster according to the position of the scattering cluster.

Specifically, under the condition that a uniform area array is configured at the ground end and a large-scale uniform area array is configured at the unmanned aerial vehicle end, the distance between a scattering cluster and the large-scale uniform area array is determined

Classifying large-scale MIMO unmanned aerial vehicle channel multipath scattering clusters into far-field scattering clusters

And near field scattering clusters

Wherein L is _a Indicating the array antenna aperture and lambda indicates the carrier wavelength.

In step 1022, optionally, a far-field channel response matrix of the transceiving end array domain is constructed based on the array response matrices respectively corresponding to the sub-arrays of the transmitting end under the far-field condition; wherein, the guide vector structure under the stable condition of plane wave includes: and the array response matrixes correspond to the sub-arrays of the transmitting end under the far-field condition respectively.

Specifically, the array response matrix corresponding to the sub-array (l, k) of the transmitting end under far-field condition is:

wherein, U ^(l,k) Represents an array response matrix, P, corresponding to the transmit terminal array (l, k) under far field conditions _h Indicating the number of rows, P, of antenna elements at the transmitting end _v Indicating the number of columns of antenna elements at the transmitting end,

indicating a transmitting terminal array (l, k) _{(l＝1,k＝1)} The spatial frequency in the vertical direction corresponds to the scatterer,

indicating the transmitting terminal array (l, k) _{(l＝1,k＝1)} The spatial frequency of the scattering body in the horizontal direction corresponds to the spatial frequency of the scattering body, L represents the number of subarrays contained in each row of the emitting end array, K represents the number of subarrays contained in each column of the emitting end array, L =1.

the doppler frequency offset at time t is:

wherein v is _T Representing the three-dimensional velocity vector, v, of the transmitting end _R Representing the receiving end three-dimensional velocity vector.

The receiving end array response matrix is:

wherein the content of the first and second substances,

a response matrix of the receiving-end array is represented,

indicating that the scatterers at the transmitting end correspond to spatial frequencies in the horizontal direction,

indicating that the scatterers at the transmitting end correspond to spatial frequencies in the vertical direction,

indicating that the receiver-side scatterer corresponds to a horizontal spatial frequency,

d _h denotes the array horizontal antenna element spacing, r _R,n,m A unit vector of the last-hop scatterer in the local coordinate system relative to the first receiving-end antenna unit is represented,

indicating that the receiver-side scatterers correspond to vertical spatial frequencies,

d _v indicating the antenna element spacing in the vertical direction of the array.

Constructing a far-field channel response matrix of a transceiving end array domain based on the above expressions (3), (4) and (5):

wherein H ^F (t, f) represents a far-field channel response matrix of the transceiving end array domain,

denotes the total number of scattering clusters, M _n Denotes the total number of sub-paths, beta _n,m Representing the amplitude of the mth sub-path in the nth scattering cluster, f representing the carrier frequency, v _n,m (t) denotes the Doppler shift at time t, τ _n,m (t) represents the time delay of the mth sub-path in the nth scattering cluster at the time t, phi _n,m And the initial phase of the mth sub-path in the nth scattering cluster is shown, vec (V) shows a vectorized receiving end array response matrix, and vec (Ul, k) shows an array response matrix corresponding to the transmitting terminal array (l, k) under the vectorized far-field condition.

In step 1023, optionally, a near-field channel response matrix of the array domain of the transceiving end is constructed based on the array response matrix corresponding to each sub-array of the transmitting end under the near-field condition; wherein, the guiding vector structure under the non-stationary condition of spherical wave includes: the array response matrix corresponding to each sub-array of the transmitting terminal under the near-field condition comprises a life-kill factor corresponding to each sub-array of the transmitting terminal under the near-field condition.

Specifically, the array response matrix corresponding to the sub-array (l, k) at the transmitting end under the near-field condition is:

the extinction factor corresponding to the transmitting terminal array (l, k) under the near field condition is:

the array emergence and extinction matrix corresponding to the mth scatterer in the nth scattering cluster is as follows:

the vertical direction array extinction factor vector is:

the array extinction factor vector in the horizontal direction is:

represents an array response matrix, Λ, corresponding to the transmit terminal array (l, k) under near field conditions _n,m An array generating and extinguishing matrix corresponding to the mth scatterer in the nth scattering cluster is shown,

the occurrence factor represents a corresponding occurrence and extinction factor of the transmitting terminal array (l, k) under the near field condition, and the occurrence factor represents whether each subarray of the transmitting terminal is visible to the scatterer under the near field condition based on the occurrence and extinction process, for example:

the value is 1, which indicates that the kth row and the lth column subarray at the transmitting end can be seen from the scatterer under the near field condition based on the life-time process,

the value is 0, which indicates that the kth row and the l column subarrays at the transmitting end are invisible to the scatterer under the near field condition based on the life-time process,

representing the vertical direction array extinction factor vector,

an array birth and death factor vector representing the horizontal direction,

is expressed as length of

The vector of all zeros of (c) is,

is expressed as length of

The vector of all zeros of (a) is,

is expressed as length of

Is the full one-vector of (a),

the serial number of the first transmitting terminal array in the visual range of the scatterer in the horizontal direction is shown,

the serial number of the first transmitting terminal array in the visual range of the scatterer in the vertical direction is shown,

the serial number of the last transmitting terminal array in the visual range of the horizontal scatterer is shown,

the serial number of the last transmitting terminal array in the visual range of the vertical scatterer is shown,

representing the spatial frequencies of the transmission terminal arrays (l, k) and the scatterers in the vertical direction,

a unit vector representing a first-hop scatterer in a local coordinate system with respect to the transmission terminal array (l, k),

representing the horizontal spatial frequency of the transmission terminal array (l, k) corresponding to the scatterer,

constructing a near-field channel response matrix of the transceiving end array domain according to expressions (4), (5) and (7) - (11):

wherein HN (t, f) represents a near-field channel response matrix of the transceiving end array domain,

an array response matrix corresponding to the terminal array (l, k) is transmitted under a vectorized near-field condition.

In step 1024, the far-field channel response matrix and the near-field channel response matrix of the transceiving end array domain are superimposed by the following expression to obtain a channel response matrix of the transceiving end array domain:

H(t,f)＝H ^F (t,f)+H ^N (t,f) (13)

where H (t, f) denotes a channel response matrix of the transceiving end array domain.

In this embodiment, first, a large-scale MIMO unmanned aerial vehicle channel multipath scattering cluster is divided into a far-field scattering cluster and a near-field scattering cluster; then, aiming at the far-field scattering cluster, acquiring far-field channel response of a receiving and transmitting end array domain based on a guide vector structure under a stable condition of plane waves; the near-field channel response of the receiving and transmitting end array domain is obtained based on the guide vector structure under the non-stable condition of the spherical wave for the near-field scattering clusters, and the channel response is obtained by adopting different modes for different scattering clusters, so that the accuracy of channel simulation can be improved.

Optionally, in step 103, the beam-domain switching matrix includes: a wave beam domain conversion matrix of a receiving end and a wave beam domain conversion matrix of a transmitting end; the following steps are also included between step 102 and step 103:

step 201, determining a kronecker product of a beam domain conversion matrix of a receiving end in a pitching direction and a beam domain conversion matrix in a horizontal direction as the beam domain conversion matrix of the receiving end;

step 202, determining a kronecker product of a beam domain conversion matrix of each transmitting terminal array in a pitching direction and a beam domain conversion matrix in a horizontal direction as a beam domain conversion matrix of the transmitting terminal array;

step 203, determining a block diagonal matrix composed of the beam domain transformation matrices of the different transmit terminal arrays as the beam domain transformation matrix of the transmitting terminal.

In step 201, a beam domain switching matrix of the receiving end is determined by expression (14):

wherein, V _B A beam domain transformation matrix representing the receiving end,

a beam domain transformation matrix in the elevation direction of the receiving end is represented,

representing the beam domain transformation matrix of the receiving end in the horizontal direction.

Determining a beam domain conversion matrix of the receiving end in the horizontal direction by expressions (15) to (17):

representing the beam domain transformation matrix, Q, of the receiving end in the horizontal direction _h The number of units per line of the receiving-end antenna array is shown,

represents the spatial frequency corresponding to the ith horizontal beam of the beam domain of the receiving end,

to represent

The corresponding array response vector is then used to,

representing a collection of complex numbers.

Determining a beam domain conversion matrix of the receiving end in the elevation direction through the following expression:

wherein the content of the first and second substances,

representing a beam domain transformation matrix, Q, of the receiving end in elevation _v The number of elements of each column of the receiving-end antenna array is represented,

representing the spatial frequency corresponding to the jth elevation beam,

to represent

The corresponding array response vector.

In step 202, a beam-domain switching matrix of the transmit terminal array (l, k) is determined by expression (21):

a beam domain transformation matrix representing the array of transmit terminals (l, k),

a beam domain transformation matrix representing the elevation direction of the transmit terminal array (l, k),

represents the beam domain transformation matrix of the transmit terminal array (l, k) in the horizontal direction.

Determining a beam domain conversion matrix of the transmission terminal array (l, k) in the elevation direction by expressions (22) to (24):

wherein the content of the first and second substances,

a beam domain transformation matrix representing the transmit terminal array (l, k) in elevation,

representing the spatial frequency corresponding to the jth elevation beam for said transmit terminal array (l, k),

to represent

The corresponding array response vector.

Determining a beam domain conversion matrix of the transmission terminal array (l, k) in the elevation direction by expressions (25) to (27):

a beam domain transformation matrix representing the horizontal direction of said transmit terminal array (l, k),

representing the spatial frequency corresponding to the i' th horizontal beam for said array of transmit terminals (l, k),

represent

The corresponding array response vector.

In step 203, the block diagonal matrix composed of the beam domain transform matrices of the different transmit terminal arrays is:

determining a beam domain switching matrix of a transmitting end by expression (29):

wherein the content of the first and second substances,

a beam domain transformation matrix representing the transmitting end.

In this embodiment, a beam domain transform matrix of the receiving end and a beam domain transform matrix of the transmitting end are respectively constructed, where the beam domain transform matrix of the receiving end is used to transform a channel response matrix of an array domain of the receiving end to a channel response matrix of a beam domain of the receiving end, and the beam domain transform matrix of the transmitting end is used to transform a channel response matrix of an array domain of the transmitting end to a channel response matrix of a beam domain of the transmitting end.

Optionally, step 103 comprises: and multiplying the beam domain switching matrix of the receiving end, the channel response matrix of the array domain of the transmitting and receiving ends and the beam domain switching matrix of the transmitting end in sequence to obtain a first channel response matrix of the beam domain of the transmitting and receiving ends.

Specifically, the conversion process of step 103 can be expressed as:

wherein H _B (t, f) a first channel response matrix, V, representing the beam domain of the transceiving end _B Represents a beam domain transformation matrix of the receiving end,

denotes V _B The conjugate transpose matrix of (a) is,

a beam-domain transformation matrix, H, representing the transmitting end ^F (t, f) represents the far-field channel response matrix of the transmit-receive array domain, H ^N (t, f) represents a near-field channel response matrix of the transceiving end array domain, H ^F (t,f)+H ^N (t, f) is a channel response matrix of the transceiving end array domain,

a far-field channel response matrix representing a transceiving end beam domain,

a near field channel response matrix representing a transceiving end beam domain.

Specifically, the impulse function approximation process of step 103 can be expressed as:

represents the far-field channel response of the nonzero channel element at the qth row and the pth column of the beam field at the transceiving end,

to represent

The (c) th row (q) of (c),

to represent

The p-th column of (2),

to represent

The conjugate matrix of (a) is determined,

indicating that the i' th horizontal beam of the receiver scatterer corresponds to a spatial frequency,

indicating that the jth elevation beam of the receiver scatterer corresponds to a spatial frequency,

representing the near field channel response of non-zero channel elements at the qth row and the pth column of the transceiving end beam field,

representing the extinction factor corresponding to the transmission terminal array (l, k) under the near field condition,

representing the propagation distance difference between the transmitting terminal array (l, k) and the sub-array (1, 1),

representing the spatial frequency of the transmission terminal array (l, k) and the scatterer in the horizontal direction,

hair with indicationThe emitter terminal arrays (l, k) correspond to the scatterers in the vertical direction of spatial frequency.

When a large-scale antenna array antenna unit is configured sufficiently, according to the law of lobida, the f-functions in the above expressions (31) and (32) can be approximated to impulse functions, and under the condition of impulse function approximation, each scatterer generates a response only on a beam with the closest value, and sparsity of a second channel response matrix of a receiving and transmitting end beam domain is generated. That is, under the condition of impulse function approximation, the sparsity of the beam domain channel of the massive MIMO unmanned aerial vehicle can be modeled.

Optionally, in step 104, at each simulation time, updating the scattering cluster parameters includes the following sub-steps:

1041, generating an attitude angle of the unmanned aerial vehicle at each simulation moment; wherein, unmanned aerial vehicle attitude angle includes: pitch angle, yaw angle, and roll angle;

step 1042, constructing a coordinate rotation matrix based on the attitude angle of the unmanned aerial vehicle;

step 1043, calculating scattering cluster parameters under a local coordinate system based on the coordinate rotation matrix;

and step 1044, updating scattering cluster parameters in a local coordinate system.

In step 1041, at each simulation instant, an unmanned aerial vehicle attitude angle may be generated through the euler angle, the unmanned aerial vehicle attitude angle including: pitch (γ), yaw (α), and roll (ω).

Owing to receive mechanical vibration and air current influence down, unmanned aerial vehicle attitude angle can produce periodic variation, and according to the cycle and the range of angular variation, the angle of pitch can be modelled as:

wherein σ _γ Amplitude of pitch angle ∈ _γ Vibration frequency, theta, of pitch angle _γ The initial phase of a pitch angle in the vibration process;

similarly, the yaw and roll angles may be modeled as:

α＝σ _α cos(2π∈ _α t+θ _α ) (36)

wherein σ _α Is the amplitude of the yaw angle, e _α Vibration frequency, theta, being yaw angle _α The initial phase of the yaw angle in the vibration process;

ω＝σ _ω cos(2π∈ _ω t+θ _ω ) (37)

wherein σ _ω For the amplitude of the roll angle, E _ω The frequency of vibration being the roll angle, theta _ω Is the initial phase of the roll angle during vibration.

In step 1042, a coordinate rotation matrix is constructed by expression (38):

wherein gamma, alpha and omega respectively represent a pitch angle, a yaw angle and a roll angle in the attitude angle of the unmanned aerial vehicle, and R represents a coordinate rotation matrix corresponding to the attitude angle of the unmanned aerial vehicle.

In step 1043, according to the scattering cluster coordinates in the global coordinate system and the coordinate rotation matrix corresponding to the attitude angle of the unmanned aerial vehicle, the scattering cluster coordinates in the local coordinate system can be calculated, where the unmanned aerial vehicle is used as the origin of coordinates, the antenna array orientation is used as the x-axis, the array horizontal direction is used as the y-axis, and the vertical direction is the z-axis.

Specifically, the scattering cluster coordinates of the mth minor diameter in the nth scattering cluster in the local coordinate system are calculated by expressions (39) and (40):

wherein the content of the first and second substances,

representing the first-hop scatterer coordinates under the local coordinate system,

representing the first hop scatterer coordinates under the global coordinate system,

representing the transmit end coordinates in the global coordinate system.

Wherein the content of the first and second substances,

representing the scatterer coordinates of the last hop under the local coordinate system,

representing the last hop scatterer coordinates under the global coordinate system,

representing the receiving end coordinates in the global coordinate system.

Subsequently, a unit vector of the scatterer in the local coordinate system with respect to each transmission terminal array (l, k) can be obtained as:

the modes representing the vectors of the scattering clusters, i.e.

And the coordinates of the first antenna unit of the k-th row and l-column sub-array of the transmitting terminal in the local coordinate system are shown.

The unit vector of the scatterer under the local coordinate system relative to each receiving end antenna unit can be obtained as follows:

wherein d is _R,n,m The modes representing the vectors of scattering clusters, i.e.

And the coordinates of the first antenna unit at the receiving end in the local coordinate system are shown.

In step 1044, the scattering cluster parameters in the local coordinate system may be updated according to the time-varying trajectory of the transceiving end.

Specifically, the process of updating the scattering cluster parameters in the local coordinate system can be expressed as:

where Δ t represents the simulation time interval.

It should be noted that other scattering cluster parameters including time delay, power, phase, etc. are also updated accordingly.

In this embodiment, the scattering cluster parameters in the global coordinate system are converted into the scattering cluster parameters in the local coordinate system through the coordinate rotation matrix corresponding to the attitude angle of the unmanned aerial vehicle, and the scattering cluster parameters in the local coordinate system are updated at each simulation moment, so that the real-time accuracy of the scattering cluster parameters can be improved.

The superiority of the BDCM protocol is verified below by experimental comparison of the BDCM protocol with the GBSM protocol.

BDCM (Beam Domain Channel Model), i.e. the unmanned aerial vehicle communication Beam Domain Channel simulation scheme proposed in this embodiment.

GBSM (Geometry-Based Stochastic Channel Model) scheme, that is, the existing unmanned aerial vehicle Channel simulation scheme.

The simulation scene selects an urban macrocell scene, the frequency band is selected to be a millimeter wave 11GHz frequency band, and the number of scattering clusters is set to be 20.

Fig. 4a, fig. 4b, and fig. 4c respectively show amplitude contrast graphs of beam domain channel responses under different array sizes, and it can be seen that as the number of antenna arrays increases, beam domain channels become sparse gradually, and a sparse effect can be achieved under a 32 × 32 uniform area array configuration. In the BDCM scheme, when a large-scale antenna array antenna unit is configured to be enough, the simulation complexity of a beam domain channel can be greatly reduced through impulse function approximation.

The model complexity of BDCM and GBSM is analyzed below with real operands, respectively.

In the BDCM scheme, the beam response calculation of each scattering cluster only needs to match horizontal and vertical beams according to spatial frequency, and carries out calculation and assignment on the amplitude and phase of the beams, and the required calculation complexity is as follows:

C _B ＝N(t)M _n ·LK·C _B,S (45)

wherein, C _B Representing the simulation complexity of the BDCM scheme at each time instant, N (t) representing the number of scattering clusters at time instant t, M _n Representing the number of sub-paths in each scattering cluster, LK representing the total number of transmit terminal arrays, C _B,S Representing the computational complexity required for each scatterer in the BDCM scheme.

According to impulse function approximation and expressions (31) and (32), each scatterer needs 1 vector subtraction operation (3 real number operations), 1 vector modulo operation (6 real number operations), 4 vector point multiplication operations (12 real number operations), 2 beam matching operations (8 real number operations are needed in total for matching the spatial frequency of the scatterer and the closest beam at the transmitting and receiving end), 1 exponential operation (15 real number operations are needed), and 1 assignment operation (1 real number operation is needed). Thus, the required computational complexity is:

C _B,S ＝3+6+12+8+15+1＝45 (46)

in the equivalent GBSM scheme, the amplitude and phase of each antenna element response need to be calculated and assigned, and the required calculation complexity is:

C _G ＝N(t)M _n M _T M _R ·C _G,A +LK·C _G,S (47)

wherein, C _G Representing the simulation complexity, M, of the equivalent GBSM scheme at each time instant _T Representing the number of antenna elements, M, at the transmitting end _R Indicating the number of antenna elements at the receiving end, C _G,A Representing the computational complexity, C, required for each scatterer in an equivalent GBSM scheme _G,S Representing the computational complexity of each sub-array parameter operation in the equivalent GBSM scheme.

Each scatterer needs 4 real number multiplication operations (needs 4 real number operations), 1 addition budget (needs 1 real number operation), 1 exponential operation (needs 15 real number operations), and 1 assignment operation (needs 1 real number operation), and the required computational complexity is:

C _G,A ＝4+1+15+1＝21 (48)

each subarray parameter operation requires 1 vector subtraction operation (requiring 3 real number operations), 1 vector modulo operation (6 real number operations), 4 vector point multiplication operations (12 real number operations), and 2 real number multiplication operations (requiring 2 real number operations), with the required computational complexity:

C _G,S ＝3+6+12+2＝23 (49)

fig. 5a shows four simulation complexity curves, respectively: the equivalent GBSM model considers the simulation complexity curves for Non-Stationary (NS) and Spherical Wave (SWF) characteristics of the array domain, the equivalent GBSM model considers the simulation complexity curves for Wide-Sense Stationary (WSS) and Plane Wave (PWF) characteristics of the array domain, the BDCM model considers the simulation complexity curves for NS and SWF characteristics of the array domain, and the BDCM model considers the simulation complexity curves for WSS and PWF characteristics of the array domain. As shown in fig. 5a, the BDCM model is significantly less complex. Meanwhile, when NS and SWF characteristics of the array domain are considered, complexity may increase.

Fig. 5b shows four simulation evaluation curves of channel capacity, which are: the channel capacity simulation evaluation curve when the equivalent GBSM model considers the NS and SWF characteristics of the array domain, the channel capacity simulation evaluation curve when the equivalent GBSM model considers the WSS and PWF characteristics of the array domain, the channel capacity simulation evaluation curve when the BDCM model considers the NS and SWF characteristics of the array domain, and the channel capacity simulation evaluation curve when the BDCM model considers the WSS and PWF characteristics of the array domain. As shown in fig. 5b, the BDCM model and the equivalent GBSM model are equivalent when applied to system performance evaluation, and at the same time, the channel capacity is slightly improved under the influence of the spherical wave and the non-stationary characteristic, which proves to be necessary to consider the spherical wave and the non-stationary characteristic in channel modeling.

In addition, as the BDCM model distributes the multipath clusters to different beams according to different angle parameters, the effective multipath number in a single beam is greatly reduced, and the small-scale fading caused by multipath propagation can be obviously inhibited. Accordingly, the influence of the doppler effect on the channel is also significantly reduced.

The theoretical derivation of the temporal autocorrelation function can be expressed as "

Wherein, gamma is _pq (Δ t; f) represents the corresponding time autocorrelation function at frequency f.

The simulation result can be obtained by directly calculating the correlation coefficient of the channel response at different time by the correlation function in Matlab.

Fig. 6a shows a schematic diagram of the time autocorrelation function of the BDCM model and the equivalent GBSM model. As shown in fig. 6a, the time dependence of the BDCM model is significantly higher than that of the equivalent GBSM model under the same simulation parameter settings.

FIG. 6b shows a schematic diagram of the Doppler spread of the BDCM model and the equivalent GBSM model. As shown in fig. 6b, it can be found from the simulation of doppler spread that the BDCM simulated doppler spread is significantly lower than the equivalent GBSM doppler spread.

From fig. 6a and fig. 6b, it is proved that the simulation result of the BDCM model has more significant time correlation, and the BDCM model is more suitable for predicting the time series of the channel compared to the equivalent GBSM model.

The unmanned aerial vehicle communication beam domain channel simulation device provided by the invention is described below, and the unmanned aerial vehicle communication beam domain channel simulation device described below and the unmanned aerial vehicle communication beam domain channel simulation method described above can be referred to in a mutually corresponding manner.

Referring to fig. 7, fig. 7 is a schematic structural diagram of an unmanned aerial vehicle communication beam domain channel simulation apparatus provided in the present invention. As shown in fig. 7, the drone communication beam domain channel simulation apparatus provided by the present invention may include:

the model building module 10 is used for building an unmanned aerial vehicle communication channel scene model, and the unmanned aerial vehicle communication channel scene model comprises scattering cluster parameters;

the matrix building module 20 is configured to build a channel response matrix of a transceiving end array domain for a large-scale MIMO unmanned aerial vehicle channel;

a matrix conversion module 30, configured to convert, based on a beam domain conversion matrix, a channel response matrix of the transceiving end array domain into a first channel response matrix of the transceiving end beam domain, and approximate a preset function in the first channel response matrix of the transceiving end beam domain to an impulse function, so as to obtain a second channel response matrix of the transceiving end beam domain;

and the channel simulation module 40 is configured to update the scattering cluster parameter at each simulation time, and calculate a channel response of the nonzero channel element in the receiving and transmitting end beam field at the current simulation time based on the second channel response matrix of the receiving and transmitting end beam field until a preset simulation time length is reached.

Optionally, the matrix building module 20 includes:

the dividing unit is used for dividing the large-scale MIMO unmanned aerial vehicle channel multipath scattering cluster into a far-field scattering cluster and a near-field scattering cluster;

the first construction unit is used for constructing a far-field channel response matrix of a receiving and transmitting end array domain based on a guide vector structure under a plane wave stationary condition;

the second construction unit is used for constructing a near-field channel response matrix of the receiving and transmitting end array domain based on the guide vector structure under the non-stationary condition of the spherical wave;

and the superposition unit is used for superposing the far-field channel response matrix and the near-field channel response matrix of the transceiving end array domain to obtain the channel response matrix of the transceiving end array domain.

Optionally, the dividing unit is specifically configured to:

Optionally, the first building unit is specifically configured to:

constructing a far-field channel response matrix of a receiving and transmitting end array domain based on array response matrixes corresponding to all sub-arrays of a transmitting end under a far-field condition; wherein the guide vector structure under the plane wave stationary condition comprises: and the array response matrixes respectively correspond to the sub-arrays of the transmitting end under the far-field condition.

Optionally, the second building unit is specifically configured to:

Optionally, the beam-domain switching matrix includes: a wave beam domain conversion matrix of a receiving end and a wave beam domain conversion matrix of a transmitting end;

the matrix conversion module 30 is further configured to:

and determining a block diagonal matrix composed of the beam domain switching matrices of the different transmitting terminal arrays as the beam domain switching matrix of the transmitting terminal.

Optionally, the matrix conversion module 30 is specifically configured to:

and multiplying the wave beam domain switching matrix of the receiving end, the channel response matrix of the array domain of the transmitting and receiving end and the wave beam domain switching matrix of the transmitting end in sequence to obtain a first channel response matrix of the wave beam domain of the transmitting and receiving end.

Optionally, the channel simulation module 40 is specifically configured to:

and updating the scattering cluster parameters in the local coordinate system.

Fig. 8 illustrates a physical structure diagram of an electronic device, and as shown in fig. 8, the electronic device may include: a processor (processor) 810, a communication Interface 820, a memory 830 and a communication bus 840, wherein the processor 810, the communication Interface 820 and the memory 830 communicate with each other via the communication bus 840. Processor 810 may invoke logic instructions in memory 830 to perform a drone communication beam domain channel emulation method comprising:

aiming at a large-scale MIMO unmanned aerial vehicle channel, constructing a channel response matrix of a transmitting and receiving end array domain;

In addition, the logic instructions in the memory 830 may be implemented in software functional units and stored in a computer readable storage medium when the logic instructions are sold or used as independent products. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.

In another aspect, the present invention also provides a computer program product, the computer program product including a computer program, the computer program being storable on a non-transitory computer readable storage medium, wherein when the computer program is executed by a processor, a computer is capable of executing the method for drone communication beam domain channel simulation provided by the above methods, the method including:

and updating the scattering cluster parameters at each simulation time, and calculating the channel response of the nonzero channel element at the current simulation time in the wave beam domain of the transmitting and receiving end based on the second channel response matrix of the wave beam domain of the transmitting and receiving end until a preset simulation time length is reached.

In yet another aspect, the present invention also provides a non-transitory computer-readable storage medium having stored thereon a computer program, which when executed by a processor, implements a method for drone communication beam-domain channel simulation provided by the above methods, the method comprising:

based on a wave beam domain conversion matrix, converting a channel response matrix of the receiving and transmitting end array domain into a first channel response matrix of the receiving and transmitting end wave beam domain, and approximating a preset function in the first channel response matrix of the receiving and transmitting end wave beam domain to an impulse function to obtain a second channel response matrix of the receiving and transmitting end wave beam domain;

The above-described embodiments of the apparatus are merely illustrative, and the units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment. One of ordinary skill in the art can understand and implement it without inventive effort.

Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware. With this understanding in mind, the above-described technical solutions may be embodied in the form of a software product, which can be stored in a computer-readable storage medium such as ROM/RAM, magnetic disk, optical disk, etc., and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the methods described in the embodiments or some parts of the embodiments.

Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, and not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.

Claims

1. An unmanned aerial vehicle communication beam domain channel simulation method is characterized by comprising the following steps:

2. The UAV communication beam domain channel simulation method of claim 1, wherein the constructing a channel response matrix of a transceiving end array domain for a massive multiple-input multiple-output (MIMO) UAV channel comprises:

constructing a far-field channel response matrix of a transceiving end array domain based on a guide vector structure under the stable condition of plane waves;

3. The method of claim 2, wherein the dividing of the massive MIMO drone channel multipath scattering clusters into far-field scattering clusters and near-field scattering clusters comprises:

under the condition that a uniform area array is configured at the ground end and a large-scale uniform area array is configured at the unmanned aerial vehicle end, dividing the large-scale MIMO unmanned aerial vehicle channel multipath scattering cluster into a far field scattering cluster and a near field scattering cluster according to the position of the scattering cluster.

4. The unmanned aerial vehicle communication beam domain channel simulation method of claim 2, wherein the constructing a far-field channel response matrix of a transceiving end array domain based on a steering vector structure under a plane wave stationary condition comprises:

5. The unmanned aerial vehicle communication beam domain channel simulation method of claim 2, wherein the constructing a near-field channel response matrix of a transceiving end array domain based on a steering vector structure under a spherical wave non-stationary condition comprises:

constructing a near-field channel response matrix of a transceiving end array domain based on array response matrixes corresponding to all sub-arrays of a transmitting end under a near-field condition; wherein, the guiding vector structure under the non-stationary condition of the spherical wave comprises: the array response matrix corresponding to each sub-array of the transmitting terminal under the near-field condition comprises a birth and death factor corresponding to each sub-array of the transmitting terminal under the near-field condition.

6. The method of claim 1, wherein the beam-domain switching matrix comprises: a wave beam domain conversion matrix of a receiving end and a wave beam domain conversion matrix of a transmitting end;

the method further comprises the following steps:

7. The UAV communication beam domain channel simulation method of claim 5, wherein the converting the channel response matrix of the transceiving end array domain into the first channel response matrix of the transceiving end beam domain based on the beam domain conversion matrix comprises:

8. The method according to claim 1, wherein the updating the scattering cluster parameters at each simulation time includes:

and updating the scattering cluster parameters in the local coordinate system.

9. An unmanned aerial vehicle communication beam field channel simulation device, characterized by includes:

the matrix construction module is used for constructing a channel response matrix of a transceiving end array domain aiming at a large-scale multi-input multi-output MIMO unmanned aerial vehicle channel;

10. An electronic device comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein the processor when executing the program implements the drone communication beam domain channel simulation method of any one of claims 1 to 8.

11. A non-transitory computer readable storage medium having stored thereon a computer program, wherein the computer program when executed by a processor implements the drone communication beam-domain channel simulation method of any one of claims 1 to 8.