CN110620627A - Non-stationary channel modeling method and device for vehicle-to-vehicle multi-antenna system - Google Patents
Non-stationary channel modeling method and device for vehicle-to-vehicle multi-antenna system Download PDFInfo
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Abstract
In order to solve the problems of the prior art, the present disclosure provides a non-stationary channel modeling method and apparatus for a vehicle-to-vehicle multi-antenna system, which can build a high-precision channel model. A method of non-stationary channel modeling for a vehicle-to-vehicle multi-antenna system, comprising: establishing a double-ring model by taking the transmitting end and the receiving end as circle centers; establishing a semi-ellipsoid model by taking a transmitting end and a receiving end as focuses; obtaining a direct path, a single-shot path and a bishot path based on the double-ring model and the semi-ellipsoid model; obtaining a channel impulse response function from a transmitting end to a receiving end based on a direct path, a single-ray path and a double-ray path; a spatio-temporal correlation function is obtained based on a channel impulse response function. The channel model is established based on the direct path, the single-ray path and the double-ray path, the accuracy of the established model is higher, and the characteristics of the V2V MIMO channel can be well represented.
Description
Technical Field
The present disclosure relates to the field of communications, and in particular, to a method and an apparatus for modeling a non-stationary channel of a vehicle-to-vehicle multi-antenna system.
Background
In recent years, massive MIMO (multiple input multiple output) multiple antenna wireless communication technology has been the focus of research because of its advantage of greatly improving spectral efficiency and system capacity. Meanwhile, vehicle-to-vehicle (V2V) communication is considered one of indispensable parts of intellectualization. Therefore, it is very beneficial for the fifth generation wireless communication network (5G) to consider adopting the MIMO multi-antenna wireless communication technology in the V2V communication system (the V2V communication system adopting the MIMO multi-antenna wireless communication technology is simply referred to as a vehicle-to-vehicle multi-antenna system herein). The existing relevant documents already provide a geometric modeling method of the MIMO channel under the V2V scene, but the model established according to the modeling method of the prior art has low precision and cannot accurately represent the characteristics of the V2V MIMO channel.
Disclosure of Invention
In order to solve at least one of the above technical problems, the present disclosure provides a non-stationary channel modeling method and apparatus for a vehicle-to-vehicle multi-antenna system, which improves the high accuracy of a channel model.
In one aspect of the disclosure, a method for modeling a non-stationary channel of a vehicle-to-vehicle multi-antenna system includes:
establishing a double-ring model by taking the transmitting end and the receiving end as circle centers;
establishing a semi-ellipsoid model by taking a transmitting end and a receiving end as focuses;
obtaining a direct path, a single-shot path and a bishot path based on the double-ring model and the semi-ellipsoid model;
obtaining a channel impulse response function from a transmitting end to a receiving end based on a direct path, a single-ray path and a double-ray path;
a spatio-temporal correlation function is obtained based on a channel impulse response function.
Optionally, the visible gains of the single-ray path and the double-ray path are calculated according to a Hata model path loss formula, and the single-ray path and the double-ray path with the visible gains smaller than the threshold gain are screened out.
Optionally, the channel impulse response function is:
in the above formula, the first and second carbon atoms are,representing the direct path component;the components of the single-ray path are represented,representing the bijective path component;
wherein the content of the first and second substances,
in the above formula, k is the Rice factor; e is a constant, j represents an imaginary number, t represents a time variable,representing the doppler shift of the direct path component,a receive phase representing the direct path component; piAnd PDBIs a normalized power correlation coefficient satisfyingIs a scatterer Ni' and transmitting terminal MTMaximum doppler shift in between;is a scatterer Ni' and receiving end MRMaximum doppler shift in between;is composed ofAzimuth in the x-y plane;is composed ofAzimuth in the x-y plane;is composed ofAzimuth in the x-y plane;a receive phase representing a single-ray path component; i is 1,2, 3;indicating the receive phase of the bijective path.
Optionally, the number of scatterers in each ring region in the double-ring model and the number of scatterers in the semi-ellipsoid model region are set as S, so as to optimize the spatio-temporal correlation function.
Optionally, the obtaining the space-time correlation function based on the channel impulse response function includes:
establishing a space-time function expression:
obtaining each path component of the space-time expression based on the space-time function expression and the channel impulse response function:
direct path component:
N1' Single shot path component:
N2' Single shot path component:
N3' Single shot path component:
bijective path component:
optionally, the method further includes predicting the performance of the communication system based on the spatio-temporal correlation function, or verifying the performance of the communication system based on the spatio-temporal correlation function, or performing back-end signal processing based on the spatio-temporal correlation function.
In another aspect of the present disclosure, a non-stationary channel modeling apparatus of a vehicle-to-vehicle multi-antenna system includes:
the double-ring model establishing module is used for establishing a double-ring model by taking the transmitting end and the receiving end as circle centers;
the semi-ellipsoid model establishing module is used for establishing a semi-ellipsoid model by taking the transmitting end and the receiving end as focuses;
the path acquisition module is used for acquiring a direct path, a single-shot path and a bishot path based on the double-ring model and the semi-ellipsoid model;
the channel impulse response function acquisition module is used for acquiring a channel impulse response function from a transmitting end to a receiving end based on a direct path, a single-shot path and a double-shot path;
and the space-time correlation function acquisition module is used for acquiring a space-time correlation function based on the channel impulse response function.
Optionally, the path obtaining module is further configured to calculate visible gains of the single-transmission path and the double-transmission path according to a Hata model path loss formula, and screen out the single-transmission path and the double-transmission path whose visible gains are smaller than the threshold gain.
Optionally, the apparatus further includes a spatio-temporal correlation function optimization module, configured to make the number of scatterers in each ring region in the dual-ring model and the number of scatterers in the semi-ellipsoid model region be S, and optimize the spatio-temporal correlation function.
Optionally, the apparatus further comprises a processing module, where the processing module is configured to predict performance of the communication system based on the spatio-temporal correlation function, or verify performance of the communication system based on the spatio-temporal correlation function, or perform back-end signal processing based on the spatio-temporal correlation function.
The invention establishes a double-ring model by taking a transmitting end and a receiving end as circle centers; establishing a semi-ellipsoid model by taking a transmitting end and a receiving end as focuses; obtaining a direct path, a single-shot path and a bishot path based on the double-ring model and the semi-ellipsoid model; the channel model is established based on the direct path, the single-ray path and the double-ray path, the accuracy of the established model is higher, and the characteristics of the V2V MIMO channel can be well represented.
Drawings
The accompanying drawings, which are included to provide a further understanding of the disclosure and are incorporated in and constitute a part of this specification, illustrate exemplary embodiments of the disclosure and together with the description serve to explain the principles of the disclosure.
FIG. 1 is a method flow diagram in an exemplary embodiment of the present disclosure;
FIG. 2 is a diagram of channel models in an exemplary embodiment of the present disclosure;
fig. 3 is a device connection diagram in an exemplary embodiment of the present disclosure.
Detailed Description
The present disclosure will be described in further detail with reference to the drawings and embodiments. It is to be understood that the specific embodiments described herein are for purposes of illustration only and are not to be construed as limitations of the present disclosure. It should be further noted that, for the convenience of description, only the portions relevant to the present disclosure are shown in the drawings.
It should be noted that the embodiments and features of the embodiments in the present disclosure may be combined with each other without conflict. The present disclosure will be described in detail below with reference to the accompanying drawings in conjunction with embodiments.
As illustrated in fig. 1 and 2, a method of non-stationary channel modeling for a vehicle-to-vehicle multi-antenna system, comprising:
step S1: establishing a double-ring model by taking the transmitting end and the receiving end as circle centers;
step S2: establishing a semi-ellipsoid model by taking a transmitting end and a receiving end as focuses;
step S3: obtaining a direct path, a single-shot path and a bishot path based on the double-ring model and the semi-ellipsoid model;
step S4: obtaining a channel impulse response function from a transmitting end to a receiving end based on a direct path, a single-ray path and a double-ray path;
step S5: a spatio-temporal correlation function is obtained based on a channel impulse response function.
Transmitting terminal M of the vehicle-to-vehicle multi-antenna system of the present embodimentTAnd a receiving end MRThe method is a method for establishing a channel model from k rows and l columns of a transmitting end to p rows and q columns of receiving end antenna elements.
As shown in fig. 2, in step S1, the dual-ring model includes a first ring centered on the transmitting end and a second ring centered on the receiving end, and the radius of the first ring is denoted as RtAnd the second ring radius is denoted as RrThe semi-ellipsoid model takes a transmitting end and a receiving end as two focuses of an ellipse in the model, the major and minor semi-axes of the ellipse are a and b respectively, and the focus distance is D0。
The vector of the moving speed of the transmitting terminal is recorded as vTOn the first ring with the transmitting end as the centerIs distributed with N1A moving velocity vector ofVehicle (i.e. first scatterer N)1') to a host; the receiving end moving velocity vector is denoted as vRN is distributed on the second ring taking the receiving end as the center of circle2A moving velocity vector ofVehicle (i.e. second scatterer N)2') to a host; consider a vehicle traveling along a road, assuming all speed directions are in the positive x-axis direction. Assume that the semi-ellipsoid model (semi-ellipsoid region in FIG. 2) is distributed with N3A stationary scatterer (i.e. a third scatterer N)2'). In this application, N'iRepresenting scatterers themselves, NiDenotes the number of scatterers, niIs N'iThe value of a single scatterer in the scatterer set is 1 to Ni。
The direct path in step S3 is a direct path from the transmitting end to the receiving end, the single path is a path from the transmitting end to the receiving end through one scatterer (a first scatterer, a second scatterer, or a third scatterer), and the bijective path is a path from the transmitting end to the receiving end through two scatterers (a first scatterer and a second scatterer).
According to the technical scheme, the direct path component (namely the line-of-sight component), the single-shot component of the static scatterer, the single-shot component of the movable scatterer and the secondary scattering component of the movable scatterer are combined to obtain the channel impulse response function and the space-time correlation function, so that the model precision is higher, and the model precision is closer to the actual environment of vehicle communication.
Channel impulse response hkl,pq(t) passing from the direct path component through N1′，N2′，N3The single ray path component of and through N1′N2The bijective path component of' consists of.
The concrete expression is as follows:
representing the direct path component;the components of the single-ray path are represented,representing the bijective path component. Specifically, subscript kl in the formula represents k rows and l columns of a transmitting end, pq represents p rows and q columns of a receiving end, and t represents a time variable;representing a direct path component from a transmitting end k row l column to a receiving end p row q column under a time variable t;represents the k rows and l columns of a transmitting terminal to pass through n under the time variable tiA single-shot path component of p rows and q columns to a receiving end;represents the k rows and l columns of a transmitting terminal to pass through n under the time variable t1And n2And p rows and q columns of bijective path components to the receiving end.
Wherein:
direct path component:
k is the Rice factor, e is a constant, and has a value of about 2.71828,indicating the doppler shift of the direct path,indicating a direct path divisionThe receive phase of the quantity. j represents an imaginary number, the square equals-1, and t represents a time variable. In particular, the method comprises the following steps of,represents the Doppler frequency shift of the direct path component from k rows and l columns at the transmitting end to p rows and q columns at the receiving end under the time variable t,and the receiving phase of the direct path component from k rows and l columns of the transmitting end to p rows and q columns of the receiving end under the time variable t is shown.
Single-shot path component:
k is the Rice factor, i ═ 1,2,3, PiIs a normalized power-related coefficient that is,is a scatterer Ni' and MT(MR) Maximum Doppler shift therebetween, i.e.Represents a scatterer Ni' and transmitting terminal MTThe maximum doppler shift in between is determined,represents a scatterer Ni' and receiving end MRMaximum doppler shift in between; as shown in figure 2 of the drawings, in which,is composed ofIn the x-y plane, i.e. azimuthIs composed ofIn the azimuth of the x-y plane,is composed ofAzimuth in the x-y plane;is that the k rows and l columns of the transmitter pass n under the time variable tiReceiving end M in direct path component to p rows and q columns of receiving endRThe path segment on one side, for example when i is 3,represents a scatterer N3' to the receiving end MRA segment;the receive phase, in particular,represents the k rows and l columns of a transmitting terminal to pass through n under the time variable tiAnd (3) receiving phases of the single-ray path components of p rows and q columns to the receiving end. The formula parameters in this application are named as above.
Bijective path component:
k is the Rice factor, PiAnd PDBIs a normalized power correlation coefficient satisfying Is a scatterer N1' and transmitting terminal MTThe maximum doppler shift in between is determined,is a scatterer N2' and receiving end MRMaximum doppler shift in between.A receive phase representing the bijective path component;is composed ofIn the azimuth of the x-y plane,is composed ofThe azimuth angle in the x-y plane, specifically,represents the k rows and l columns of a transmitting terminal to pass through n under the time variable t1And n2Receiving phase of bijection path component of p rows and q columns to a receiving end;is that the k rows and l columns of the transmitter pass n under the time variable t1Transmitting end M in direct path component to receiving end p rows and q columnsTOne side of the path section, i.e. the diffuser N1' (specifically, n)1) To the transmitting end MTA segment;is that the k rows and l columns of the transmitter pass n under the time variable t2Receiving end M in direct path component to p rows and q columns of receiving endRPath section of one sideI.e. scatterers N2' (specifically, n)2) To the receiving end MRAnd (4) section.
The doppler shift of each path component can be expressed as:
wherein the content of the first and second substances,<>representing the vector inner product, i.e. dot product. | | | represents a modulus value. The definition of vector inner product is used here, and the inner product of two vectors is divided by the module value of two vectors, which is equal to the cosine value of the included angle between the two vectors.Is a scatterer Ni' and MT(MR) Maximum Doppler shift therebetween, i.e.Is a scatterer N1' and MTThe maximum doppler shift in between is determined,is a scatterer N1' and MRThe maximum doppler shift in between is determined,is a scatterer N2' and MRThe maximum doppler shift in between is determined,is a scatterer N2' and TRλ c/f, the maximum doppler shift betweenc，fcIs the carrier frequency and c is the speed of light.
The receive phase of each path component can be expressed as:
wherein the initial phase Is composed ofIn the x-y plane. Taking into account stationary scatterers N3The method is used for representing high-rise buildings, trees and other real objects in the surrounding environment of the street, and the height is not negligible during modeling. Note the bookIs composed ofThe angle of elevation of (a) is,is composed ofThe spatial angle with the x-axis is:
considering the non-stationary characteristic of the channel, the time delay is denoted as τ, and the time-varying parameter is updated at time t + τ as follows:
based on large-scale loss, considering the influence of distance and path loss factors, dividing visible regions of scatterers, and selecting a Hata model path loss formula according to the street environment characteristics corresponding to a proposed model:
where dB is the unit of the number of bits,is a coefficient related to the receiving antenna, hT、hRRespectively, the height of the transmit and receive antennas, for medium-sized coverage,the values are as follows:
according to the scene characteristics of the model, h is obtainedT＝hRAnd (5) arranging to obtain a path loss calculation formula of the model:
PLHata(d)[dB]＝68.75+27.72logfc+44.9logd (19)
and (3) disregarding the power loss at the scattering point to obtain a total formula of visible gain calculation of the single-ray path and the double-ray path:
if the visible gain is larger than or equal to the threshold gain, the effective single-ray path and the effective double-ray path are reserved; if the visible gain is smaller than the threshold gain, the invalid path is screened out, and the path component is not considered when the space-time correlation function is calculated.
The space-time correlation function can describe the variation condition of the channel in time and space, characterize the channel characteristics, and calculate the expression as follows:
wherein represents a complex conjugate, E [ alpha ]]Expressing an average value; rhok′l′p′q′,klpq(t, τ) represents a correlation function between channels from k 'row/column at the transmitting end to p' row/column at the receiving end and channels from k row/column at the transmitting end to p row/column at the receiving end under the condition of time t and time delay τ.
The channel impulse response from k 'row/column at the transmitting end to p' row/column at the receiving end under the condition of time t and time delay tau is shown.
In the conventional assumption, the number of scatterers in the model tends to be infinite, and the angle of departure (AoD) and angle of arrival (AoA) are each represented by a continuously varying probability density distribution. Based on this assumption, each path component in the above equation is separately subjected to the following expansion calculation, wherein the direct path component (LoS path component):
N1’，N2' Single shot path component:
N3' Single shot path component:
bijective path component:
considering the number of scatterers in the actual scene should be limited, let N1＝N2＝N3The form of integration is adjusted to the following summation:
N1' Single shot path component:
N2' Single shot path component:
N3' Single shot path component:
bijective path component:
formula parameters can be referred to the explanations in the foregoing;
let the delay factors τ be 0 and k 'l' p 'q' be klpq, respectively, and the space-time correlation function be simplified to obtain a space-time correlation function (CCF) and a time-time correlation function (ACF), respectively.
After the space-time correlation function, the performance of the communication system can be predicted based on the space-time correlation function, the performance of the communication system is verified based on the space-time correlation function, and the back-end signal processing is carried out based on the space-time correlation function.
In this embodiment, the variation of the channel under the combined action of the stationary scatterer and the mobile scatterer is explored by combining a double-ring model and a semi-ellipsoid model (semi-ellipsoid model), and a uniform planar array is adopted for the antenna to characterize the near-field effect of the spherical wave. The visible scattering region is divided by different path losses, and the space-time correlation function is analyzed by changing parameters. The final effect can be displayed by computer simulation.
In another aspect of the present embodiment, as shown in fig. 3, a non-stationary channel modeling apparatus of a vehicle-to-vehicle multi-antenna system includes:
the double-ring model establishing module 1 is used for establishing a double-ring model by taking a transmitting end and a receiving end as circle centers;
the semi-ellipsoid model establishing module 2 is used for establishing a semi-ellipsoid model by taking the transmitting end and the receiving end as focuses;
the path acquisition module 3 is used for acquiring a direct path, a single-shot path and a bishot path based on the double-ring model and the semi-ellipsoid model;
the channel impulse response function acquisition module 4 is used for acquiring a channel impulse response function from the transmitting end to the receiving end based on a direct path, a single-shot path and a double-shot path;
and a space-time correlation function obtaining module 5, configured to obtain a space-time correlation function based on the channel impulse response function.
Optionally, the path obtaining module is further configured to calculate visible gains of the single-transmission path and the double-transmission path according to a Hata model path loss formula, and screen out the single-transmission path and the double-transmission path whose visible gains are smaller than the threshold gain.
Optionally, the apparatus further includes a spatio-temporal correlation function optimization module, configured to make the number of scatterers in each ring region in the dual-ring model and the number of scatterers in the semi-ellipsoid model region be S, and optimize the spatio-temporal correlation function.
Optionally, the apparatus further comprises a processing module, where the processing module is configured to predict performance of the communication system based on the spatio-temporal correlation function, or verify performance of the communication system based on the spatio-temporal correlation function, or perform back-end signal processing based on the spatio-temporal correlation function.
The apparatus in this embodiment is used to implement the method in the above-described embodiment, and the principle and effect of the apparatus are the same as those of the method, and the description of this embodiment is not repeated.
The embodiment provides a 3D non-stationary V2V MIMO communication channel model based on geometry for a vehicle communication scene, based on uniform planar array antenna configuration, and by using a double-ring and semi-ellipsoid model (semi-ellipsoid), the distribution of static scatterers and moving scatterers in the environment is comprehensively considered, and the number of the scatterers is subjected to finite approximation. Meanwhile, a direct path component (a line-of-sight component), a single-shot component through a static scatterer, a single-shot component through a moving scatterer and a secondary scattering component through the moving scatterer are combined, a channel impulse response and a space-time correlation function expression are deduced, and a visible region division algorithm of the scatterer is designed by taking the power attenuation degree of a transmission path as a basis. Finally, the influence of different parameters on the channel correlation is analyzed through simulation, and the result shows that the proposed model can well represent the characteristics of the V2V MIMO channel.
In the description herein, reference to the description of the terms "one embodiment/mode," "some embodiments/modes," "example," "specific example," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment/mode or example is included in at least one embodiment/mode or example of the application. In this specification, the schematic representations of the terms used above are not necessarily intended to be the same embodiment/mode or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments/modes or examples. Furthermore, the various embodiments/aspects or examples and features of the various embodiments/aspects or examples described in this specification can be combined and combined by one skilled in the art without conflicting therewith.
Furthermore, the terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one such feature. In the description of the present application, "plurality" means at least two, e.g., two, three, etc., unless specifically limited otherwise.
It will be understood by those skilled in the art that the foregoing embodiments are merely for clarity of illustration of the disclosure and are not intended to limit the scope of the disclosure. Other variations or modifications may occur to those skilled in the art, based on the foregoing disclosure, and are still within the scope of the present disclosure.
Claims (10)
1. A method of modeling non-stationary channels of a vehicle-to-vehicle multi-antenna system, comprising:
establishing a double-ring model by taking the transmitting end and the receiving end as circle centers;
establishing a semi-ellipsoid model by taking a transmitting end and a receiving end as focuses;
obtaining a direct path, a single-shot path and a bishot path based on the double-ring model and the semi-ellipsoid model;
obtaining a channel impulse response function from a transmitting end to a receiving end based on a direct path, a single-ray path and a double-ray path;
a spatio-temporal correlation function is obtained based on a channel impulse response function.
2. The method of claim 1, wherein the visible gains of the single-ray path and the double-ray path are calculated according to a Hata model path loss formula, and the single-ray path and the double-ray path with the visible gain smaller than a threshold gain are screened out.
3. The method of claim 1, wherein the channel impulse response function is:
in the above formula, the first and second carbon atoms are,representing the direct path component;the components of the single-ray path are represented,representing the bijective path component;
wherein the content of the first and second substances,
in the above formula, k is the Rice factor; e is a constant, j represents an imaginary number, t represents a time variable,representing the doppler shift of the direct path component,a receive phase representing the direct path component; piAnd PDBIs a normalized power correlation coefficient satisfying Is a scatterer Ni' and transmitting terminal MTMaximum doppler shift in between;is a scatterer Ni' and receiving end MRMaximum doppler shift in between;is composed ofAzimuth in the x-y plane;is composed ofAzimuth in the x-y plane;is composed ofAzimuth in the x-y plane;a receive phase representing a single-ray path component; i is 1,2, 3;indicating the receive phase of the bijective path.
4. The method of claim 3, wherein the spatio-temporal correlation function is optimized by taking the number of scatterers in each ring region in the double-ring model and the number of scatterers in the semi-ellipsoid model region as S.
5. The method of claim 4, wherein the obtaining the spatio-temporal correlation function based on a channel impulse response function comprises:
establishing a space-time function expression:
obtaining each path component of the space-time expression based on the space-time function expression and the channel impulse response function:
direct path component:
N1' Single shot path component:
N2' Single shot path component:
N3' Single shot path component:
bijective path component:
6. the method of claim 1, further comprising predicting communication system performance based on a spatio-temporal correlation function, or verifying communication system performance based on a spatio-temporal correlation function, or performing back-end signal processing based on a spatio-temporal correlation function.
7. A non-stationary channel modeling apparatus for a vehicle-to-vehicle multi-antenna system, comprising:
the double-ring model establishing module is used for establishing a double-ring model by taking the transmitting end and the receiving end as circle centers;
the semi-ellipsoid model establishing module is used for establishing a semi-ellipsoid model by taking the transmitting end and the receiving end as focuses;
the path acquisition module is used for acquiring a direct path, a single-shot path and a bishot path based on the double-ring model and the semi-ellipsoid model;
the channel impulse response function acquisition module is used for acquiring a channel impulse response function from a transmitting end to a receiving end based on a direct path, a single-shot path and a double-shot path;
and the space-time correlation function acquisition module is used for acquiring a space-time correlation function based on the channel impulse response function.
8. The apparatus of claim 7, wherein the path obtaining module is further configured to calculate the visible gains of the single-ray path and the double-ray path according to a Hata model path loss formula, and screen out the single-ray path and the double-ray path having the visible gains smaller than a threshold gain.
9. The apparatus of claim 7, further comprising a spatio-temporal correlation function optimization module for optimizing the spatio-temporal correlation function by setting the number of scatterers in each ring region and the number of scatterers in the semi-ellipsoidal model region in the double-ring model to S.
10. The apparatus of claim 7, wherein the apparatus further comprises a processing module for predicting communication system performance based on a spatiotemporal correlation function, or verifying communication system performance based on a spatiotemporal correlation function, or performing back-end signal processing based on a spatiotemporal correlation function.
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| CN111314001A (en) * | 2020-03-10 | 2020-06-19 | 合肥工业大学 | Geometric-based non-stationary V2V MIMO channel modeling method |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN111314001A (en) * | 2020-03-10 | 2020-06-19 | 合肥工业大学 | Geometric-based non-stationary V2V MIMO channel modeling method |
| CN111462315A (en) * | 2020-04-03 | 2020-07-28 | 北京邮电大学 | Vehicle-to-vehicle three-dimensional channel modeling method for urban combined lane scene |
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| CN112333671B (en) * | 2020-11-03 | 2022-03-18 | 合肥工业大学 | Non-stationary characteristic extraction method for vehicle-to-vehicle MIMO channel |
| CN113747401A (en) * | 2021-09-08 | 2021-12-03 | 中国银行股份有限公司 | Method and device for modeling non-stationary channel from vehicle to vehicle |
| CN114785438A (en) * | 2022-04-18 | 2022-07-22 | 中国人民解放军陆军工程大学 | Method for constructing vehicle-to-vehicle channel model in tactical communication environment and system implementation scheme |
| CN114785438B (en) * | 2022-04-18 | 2023-08-22 | 中国人民解放军陆军工程大学 | Method and system implementation scheme for constructing vehicle-to-vehicle channel model in tactical communication environment |
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