Disclosure of Invention
Aiming at the defects in the prior art, the ultra-wideband and frequency non-stationary characteristics in the unmanned aerial vehicle communication channel are comprehensively considered, the ultra-wideband unmanned aerial vehicle non-stationary MIMO channel simulation method, medium and equipment are provided, channel coefficients between any antenna pair in an unmanned aerial vehicle communication scene can be output, and the generation and evolution methods of the channel parameters are provided.
In order to achieve the above purpose, the present invention adopts the following technical scheme:
The simulation method of the ultra-wideband unmanned aerial vehicle non-stationary MIMO channel is characterized by comprising the following steps:
Inputting configuration parameters;
calculating bandwidth-related channel simulation parameters including rice factor, number of scattering clusters and number of sub-paths in the scattering clusters;
Calculating geometrically related channel simulation parameters including time delay and angle parameters of a line-of-sight path, time delay, angle parameters and power parameters of a non-line-of-sight path, attitude-related power correction factors and Doppler phases;
and obtaining a channel simulation output result by using the calculated bandwidth related and geometry related channel simulation parameters.
In order to optimize the technical scheme, the specific measures adopted further comprise:
Further, the configuration parameters include an unmanned aerial vehicle communication scene type, a carrier frequency, an antenna type, a signal bandwidth, an initial position vector and a speed vector of the unmanned aerial vehicle, a receiving end and a scatterer.
Further, the calculation process of the rice factor, the number of scattering clusters and the number of sub-paths in the scattering clusters is as follows:
1) Lais factorModeled as Gaussian random variables with an average at a given frequency point fcAnd standard deviation ofGiven that the positions of the transmitting and receiving ends are p= (xT(t),yT(t),zT(t),xR(t),yR(t),zR (T)), the upper label is T representing the transmitting end Tx, the upper label is R representing the receiving end Rx, and the rice factor is expressed as:
Wherein, Kμ is the average value at the carrier frequency of 1GHz, Kγ is the frequency-dependent correction coefficient, ωref is the frequency offset in GHz, Kε is the bandwidth-dependent correction coefficient, Kσ is the standard deviation at the carrier frequency of 1GHz, Kδ is the standard deviation of the frequency-dependent, Kκ is the standard deviation of the bandwidth-dependent, XK is the spatially-dependent gaussian distributed zero-average random variable, t represents time of day, and B represents the signal bandwidth;
2) For each scatter cluster, a K-nearest neighbor algorithm is used to calculate the core power density ρx:
Where Kx denotes the set of K multipath components closest to x, Py is the power of another arbitrary sub-path, τx/y is the delay of the sub-path, στ,Respectively representing the time delay, the azimuth of the departure angle and the standard deviation of the azimuth of the arrival angle,AndAzimuth angles of a departure angle and an arrival angle in a clustering process are respectively represented, and subscripts x and y respectively represent sub-paths x and y;
Dividing rays into different clusters by using a clustering algorithm based on the nuclear power density, so as to determine the total number N (t, B) of non-line-of-sight paths, namely the number of scattering clusters;
the number of sub-paths M (B) within a scattering cluster is statistically determined as follows:
Where Mmax is the upper bound of M (B), the parameter k represents an environmentally determined sparsity factor, cDS、cASD and cZSD are intra-cluster delay spread, intra-cluster angle spread in the horizontal direction and intra-cluster angle spread in the pitch direction, respectively, Dh and Dv are array sizes in the horizontal and vertical dimensions, respectively, and λ is the wavelength.
Further, the calculation process of the time delay and the angle parameter of the sight path is as follows:
1) Calculating a position vector of a receiving and transmitting end at the moment t:
Wherein, LT/R(t0) represents an initial position of the transmitting and receiving end, vT/R (T') represents an instantaneous speed, and represents the transmitting end Tx when the upper label is T, and represents the receiving end Rx when the upper label is R;
2) Calculating the time delay of the sight path according to the calculated position vector of the receiving and transmitting end
Where ep (t) is a vector directed from the Tx center to the p-th antenna unit, eq (t) is a vector directed from the Rx center to the q-th antenna unit, and c is a propagation velocity of electromagnetic waves;
3) According to the calculated position vector of the receiving and transmitting end, calculating the azimuth angle and the pitch angle of the departure angle and the arrival angle of the sight distance path:
In the formula,AndThe azimuth and pitch angles of the departure angle respectively,AndThe azimuth and pitch angles of the angle of arrival, ex、ey and ez, respectively, are unit vectors of the x-axis, y-axis and z-axis.
Further, the calculation process of the time delay, the angle parameter and the power parameter of the non-line-of-sight path is as follows:
1) SpecifyingTo point from the q-th antenna element of Rx to the vector of the last-hop scatterer,To be a vector pointing from the p-th antenna element of Tx to the first-hop scatterer,To connect the vector of the first-hop scatterer to the last-hop scatterer, the three vectors together form a signal propagation path:
In the formula,The p-th antenna unit of Tx, the first-hop scatterer and the last-hop scatterer form a vector triangle, and the p-th antenna unit of Tx, the q-th antenna unit of Rx and the last-hop scatterer form another vector triangle by minimizingLength of (d) to infer vectorAndTo translate the problem into the following optimization tasks:
Constraint conditions:
Wherein the minimum distance dmin is a variable customized according to the specific scene, and the value dmin is assigned to the vectorThe cosine law is then used to determine the correlation of the residual vectors as follows:
2) Determining the angle parameter of the non-line-of-sight path through the geometric relation of the vectors:
In the formula,In order to leave the azimuth of the angle,As the pitch angle of the departure angle,In order to reach the azimuth of the angle of arrival,Pitch angle, which is the angle of arrival;
3) Normalizing the power of the line-of-sight path, and then distributing the power of the mth sub-path in the nth non-line-of-sight pathThe method comprises the following steps:
where rτ denotes a delay scalar, στ denotes a delay spread, and SFc denotes cluster shadow fading following gaussian distribution;
relative power of non-line-of-sight pathsThe normalization process determines that:
Where N (t, B) and M (B) represent the number of scattering clusters and the number of sub-paths within a scattering cluster, respectively.
Further, the attitude-dependent power correction factor is modeled as:
In the formula,Represents a power correction factor, θE (t) is calculated byAs calculated, the vector set ΘE contains all direction vectors from the edge of the fuselage to the antenna element,AndRespectively represent the line-of-sight direction vector and the departure angle,Is associated withIs a vector whose azimuth angles match,Is the basis vector of the z-axis, θP (t) is calculated byAnd RP (t) is obtained as a gesture matrix.
Further, the calculation process of the Doppler phase is as follows:
1) Conversion of azimuth angle of departure angleAzimuth angle of arrivalPitch angle of departureAnd angle of arrivalIn a Cartesian coordinate system, the angle unit vectors of the sight paths of the transmitting end and the receiving end are respectively obtained as followsAndThe angle unit vector of the non-line-of-sight path of the transmitting end and the receiving end isAnd
2) Based on Doppler effect principle, calculating time-frequency-varying traditional Doppler phase components of line-of-sight paths and non-line-of-sight pathsAndThe following are provided:
In the formula,AndRespectively representing the instantaneous moving speeds of a transmitting end and a receiving end, and fc represents the carrier frequency;
3) Calculating pose-changing phase components of line-of-sight paths and non-line-of-sight pathsAndThe following are provided:
Wherein the velocity rotation matrix RR (t) is used to modify the position vector according to the change of the motion direction, and define the gesture matrix as:
Wherein ω is the roll angle,The yaw angle and the gamma angle are pitch angles;
4) Calculating equivalent Doppler phases for line-of-sight and non-line-of-sight pathsAndThe following are provided:
wherein U (0, 2 pi) is a random initial component and obeys uniform distribution on 0-2 pi.
Further, the process of obtaining the channel simulation output result is as follows:
the channel matrix containing P transmit antenna elements and Q receive antenna elements is expressed as:
Where H denotes channel fading, fc' denotes the center frequency of the signal, LPL denotes path propagation loss, LSF denotes shadow fading, t denotes time of day, τ denotes time delay, B denotes signal bandwidth, fc denotes carrier frequency,The channel impulse response combination between the P transmitting antennas and the Q receiving antennas is represented as follows:
In the formula,Represents the rice factor, N (t, B) represents the number of scattering clusters, M (B) represents the number of sub-paths within a scattering cluster,Representing the time delay of the line-of-sight path,Representing the delay of non-line-of-sight paths, delta (·) representing the dirac function, coefficientsAndIs modeled as:
In the formula,Representing the power correction factor due to blockage of the airframe structure,Representing a power correction factor associated with the path delay,AndRepresenting the equivalent doppler phases of the line-of-sight path and the non-line-of-sight path caused by motion,AndAn antenna pattern function representing a line-of-sight path and a non-line-of-sight path taking into account the change in attitude.
Accordingly, the invention provides a computer readable storage medium storing a computer program, which is characterized in that the computer program causes a computer to execute the simulation method of the ultra-wideband unmanned aerial vehicle non-stationary MIMO channel.
Correspondingly, the invention provides electronic equipment which is characterized by comprising a memory, a processor and a computer program stored on the memory and capable of running on the processor, wherein the simulation method of the ultra-wideband unmanned aerial vehicle non-stationary MIMO channel is realized when the processor executes the computer program.
The beneficial effects of the invention are as follows:
1. the invention provides an unmanned aerial vehicle channel simulation method supporting an ultra-wideband communication system, which introduces bandwidth related parameters, solves the problem of output distortion caused by the approximation of bandwidth by the traditional method, and is more consistent with a real scene;
2. The invention provides an accurate calculation method of channel parameters, supports continuous evolution of dynamic scenes, and can reflect channel non-stationarity caused by gesture and frequency change.
Detailed Description
The following description of the embodiments of the present application will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present application, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
In an embodiment, the invention provides a simulation method of an ultra-wideband unmanned aerial vehicle non-stationary MIMO channel, and the flow of the simulation method is shown in FIG. 1, and specifically comprises the following steps.
Step one, inputting user-defined parameters, namely configuration parameters, including parameters such as unmanned aerial vehicle communication scene type, carrier frequency, antenna type, signal bandwidth, initial position vector and speed vector of unmanned aerial vehicle/receiving end/scatterer, and the like, wherein the details are shown in table 1.
TABLE 1 user input parameters
And step two, calculating the channel parameters related to the bandwidth. The method specifically comprises the steps of generating a Lees factor parameter by using bandwidth corrected random distribution, and calculating the number of scattering clusters and the number of sub-paths in the scattering clusters by using a ray tracing technology.
Step 2.1, calculating the Lees factor in the ultra-wideband channel of the unmanned aerial vehicle, wherein the method comprises the following steps:
The present embodiment uses the rice factorModeled as Gaussian random variables with an average at a given frequency point fcAnd standard deviation ofGiven the positions of the transmitting end (Tx) and the receiving end (Rx) as p= (xT(t),yT(t),zT(t),xR(t),yR(t),zR (t)), the rice factor can be expressed as:
Wherein, Kμ is 15, Kγ is 2.8, omegaref is 1GHz, Kε is-8.3, Kσ is 9.85, Kδ is 1.15, Kκ is 1.4, XK is a spatially related Gaussian distribution zero-mean random variable, and the values of the Lesi factors are shown in Table 2.
Table 2 example of the values of rice factor in simulation
| Quasi-stationary section | Plateau 1 | Plateau 2 | Plateau 3 | Plateau 4 |
| Value taking | 9.6372 | 15.6094 | 7.6055 | 3.6072 |
Step 2.2, calculating the number of scattering clusters and the number of sub-paths in the scattering clusters, wherein the method comprises the following steps:
The power and time delay information of a large number of sub-paths are generated by using a ray tracing technology, the number of scattering clusters and the number of sub-paths in the scattering clusters are determined by using a clustering algorithm based on the nuclear power density, and for each cluster sample, the density is calculated by using a K-nearest neighbor algorithm:
where Kx represents the set of K multipath components closest to multipath component x, Py is the power of another arbitrary sub-path, τx/y is the delay of the sub-path, σ(·) is represented as the standard deviation of the sub-path; AndThe azimuth of the departure angle and arrival angle in the clustering process is represented. Using a clustering algorithm based on the kernel power density, rays may be split into different clusters to determine the total number of non-line-of-sight paths N (t, B). The number of sub-paths M (B) is determined through a statistical method, and the number of sub-paths affected by the bandwidth in each cluster is modeled as follows:
Where Mmax is the upper limit of M (B) entered by the user, the parameter k represents an environment-dependent sparsity factor, cDS、cASD and cZSD are intra-cluster delay spread and intra-cluster delay spread in the horizontal and pitch directions, respectively, Dh and Dv are array sizes in the horizontal and vertical dimensions in M, λ is wavelength in M, B is bandwidth in MHz.
Referring to fig. 2, in the case of the narrow band 10M, it is calculated that all rays are grouped into the same group of clusters, and as the bandwidth increases to 1GHz, the number N (t, B) of clusters is 10, and the number of sub-paths within each cluster corresponds as shown in table 3.
TABLE 3 ray-clustering results
And thirdly, calculating geometrically related channel simulation parameters including position vectors, time delay parameters, angle parameters, power parameters and Doppler phase parameters.
Step 3.1, calculating time delay and angle parameters of a Line-of-sight (LoS) path of an unmanned aerial vehicle air-ground channel, wherein the method comprises the following steps:
And 3.1.1, calculating position vectors of a receiving end, a transmitting end and a scatterer at the moment t, wherein the method comprises the following steps:
in this embodiment, the time delay of the LoS path is determined based on the geometric relationship between the receiving end and the transmitting end, and the channel parameters of the MIMO system need to be calculated separately for each element in the antenna array, and the instantaneous position vector of Tx or Rx can be expressed as:
Wherein,
Wherein, |vT/R/S |represents a module value of the moving speed of the receiving and transmitting end and the scattering body, phiT/R/S represents an azimuth angle of the moving speed of the receiving and transmitting end and the scattering body, phiT/R/S represents a pitch angle of the moving speed of the receiving and transmitting end and the scattering body, and the values are shown in table 1.
And 3.1.2, calculating the time delay of the line-of-sight path at the moment t according to the position vector of the receiving and transmitting end calculated in the step 3.1.1, wherein the method comprises the following steps:
Wherein ep (t) is a vector pointing from the Tx center to the p-th antenna unit, eq (t) is a vector pointing from the Rx center to the q-th antenna unit, c is the velocity of electromagnetic waves, and the value is 3×108 m/s. When the simulation time is 1s, the simulation device,Has a value of 0.504us.
And 3.1.3, calculating azimuth angles and pitch angles of the departure angle and the arrival angle of the LoS path according to the positions of the receiving and transmitting ends calculated in the step 3.1.1, wherein the method comprises the following steps:
In the formula,AndThe azimuth and pitch angles of the departure angle respectively,AndThe azimuth and pitch angles of the angle of arrival, ex、ey and ez, respectively, are unit vectors of the x-axis, y-axis and z-axis.
Step 3.2, calculating time delay, angle and power parameters of a non-line-of-sight (NLoS) path of an unmanned aerial vehicle air-ground channel, wherein the method comprises the following steps:
And 3.2.1, calculating a distance vector and a time delay at the moment t according to the position information of the receiving and transmitting end calculated in the step 3.1.1, wherein the method comprises the following steps:
The present embodiment specifiesTo point from the q-th antenna element of Rx to the vector of the last-hop scatterer,To be a vector pointing from the p-th antenna element of Tx to the first-hop scatterer,In order to connect the vector of the first-hop scatterer to the vector of the last-hop scatterer, the signal propagation path is composed of the three vectors.
Calculating vectors by the following optimization tasksAndLength of (2):
Constraint conditions:
Wherein, the minimum distance dmin is a variable customized according to the specific scene, and dmin is assigned to the vectorThe cosine law is then used to determine the correlation of the residual vectors:
According to the calculated distance vector of the m-th sub-path in the n NLoS paths, calculating the time delay of the NLoS paths, wherein the method comprises the following steps:
when the simulation time is 1s, the first 5 NLoS paths are selected,The values of (a) are respectively 0.537us,0.544us,0.614us,0.73us and 0.858us.
And 3.2.2, calculating azimuth angles and pitch angles of the departure angle and the arrival angle of the NLoS path according to the positions of the receiving and transmitting ends calculated in the step 3.1.1, wherein the method comprises the following steps:
In the calculation process of path delay in step 3.2.1, position vectors of a receiving end, a first hop and a last hop scatterer are defined, and the geometrical relationship of the vectors determines the corresponding angle of the NLoS path:
In the formula,In order to leave the azimuth of the angle,As the pitch angle of the departure angle,In order to reach the azimuth of the angle of arrival,Is the angle of arrival.
And 3.2.3, calculating normalized power of the LoS path and the nth NLoS path by using the propagation delay obtained in the step 3.2.1, wherein the method comprises the following steps:
After normalizing the power of the LoS path, the power distribution of the NLoS path is:
Wherein rτ represents a delay scalar, sigmaτ represents delay spread, 9.81×10-8,SFc represents cluster shadow fading obeying gaussian distribution, and the mean value is 0 and the variance is 3. The relative power of the NLoS component is then finally determined by a normalization process:
And 3.3, calculating a power correction factor related to the gesture, wherein the method comprises the following steps:
According to the positions of the unmanned plane and the ground terminal, the line-of-sight direction vectorAnd departure angleMay be determined. Furthermore, the present embodiment introduces a vector set ΘE, which contains all direction vectors from the edge of the fuselage to the antenna elements.Is associated withWhich determines the angle thetaE (t) that incorporates the unmanned attitude change depending on the attitude matrix RP (t). Thus, the present embodiment models the power correction factor as:
Wherein, thetaE (t) is a value obtained byThe calculated value of the total number of the components,Is the basis vector of the z-axis, θP (t) is calculated byObtained.
Step 3.4, calculating Doppler phase, wherein the method comprises the following steps:
step 3.4.1 azimuthal angle of the departure angleAzimuth angle of arrivalPitch angle of departureAnd angle of arrivalConverted into Cartesian coordinates to obtain angle unit vectors of LoS and NLoS paths of the transceiver endAnd
Step 3.4.2, calculating the time-frequency-variant traditional Doppler phase components of the LoS and NLoS paths, wherein the method comprises the following steps:
and 3.4.3, calculating attitude change phase components of LoS and NLoS propagation paths, wherein the method comprises the following steps:
When the rolling angle of the unmanned plane is-30 degrees, the yaw angle is-45 degrees, the pitch angle is 10 degrees, the corresponding omega= -30 degrees,Γ=10°, the calculated pose matrix is:
step 3.4.4. Calculate equivalent doppler phases of the LoS path and NLoS path, i.e. the frequency dependent path phases consist of random initial component, conventional doppler component and attitude change component, from the conventional doppler component and attitude change doppler component in steps 3.4.2 and 3.4.3, by:
wherein U (0, 2 pi) is a random initial component and obeys uniform distribution on 0-2 pi.
And step four, inputting the Lais factor, the time delay, the phase and the power coefficient obtained by calculation into an unmanned aerial vehicle space-ground channel model to obtain a channel simulation output result.
The ultra-wideband unmanned aerial vehicle MIMO channel is modeled as:
Where H denotes channel fading, B is the actual bandwidth of the signal, fc denotes the carrier frequency, fc' denotes the center frequency of the signal, LPL denotes the path propagation loss, LSF denotes shadow fading,The channel impulse response combination between the P transmitting antennas and the Q receiving antennas is represented as follows:
Wherein the coefficient isAndThe expression is as follows:
In the formula,Representing the power correction factor due to blockage of the airframe structure,Representing a power correction factor associated with the path delay,AndRepresenting the equivalent doppler phases of the line-of-sight path and the non-line-of-sight path caused by motion,AndAn antenna pattern function representing a line-of-sight path and a non-line-of-sight path taking into account the change in attitude.
In this embodiment, the receiving end and the transmitting end both adopt ideal omni-directional antennas, i.e. antenna pattern functionsAndThe value may be approximated as a constant 1. The final output channel coefficients contain the results of the different antenna pairs (as shown in fig. 3-6) and the results at different times (as shown in fig. 7-8).
In another embodiment, the present invention provides a computer readable storage medium storing a computer program, where the computer program causes a computer to execute the simulation method of the ultra wideband unmanned aerial vehicle non-stationary MIMO channel according to the first embodiment.
In another embodiment, the invention provides an electronic device, which comprises a memory, a processor and a computer program stored on the memory and capable of running on the processor, wherein the simulation method of the ultra-wideband unmanned aerial vehicle non-stationary MIMO channel is realized when the processor executes the computer program.
In the disclosed embodiments, a computer storage medium may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The computer storage medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a computer storage medium would include one or more wire-based electrical connections, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
The above is only a preferred embodiment of the present invention, and the protection scope of the present invention is not limited to the above examples, and all technical solutions belonging to the concept of the present invention belong to the protection scope of the present invention. It should be noted that modifications and adaptations to the invention without departing from the principles thereof are intended to be within the scope of the invention as set forth in the following claims.