CN115085839A - Unmanned aerial vehicle mountain terahertz channel modeling method based on ray tracing - Google Patents
Unmanned aerial vehicle mountain terahertz channel modeling method based on ray tracing Download PDFInfo
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Abstract
The invention relates to an unmanned aerial vehicle mountain terahertz channel modeling method based on ray tracing, and belongs to the technical field of terahertz communication. According to the method, the electromagnetic wave propagation path is tracked through a ray tracing method, and the propagation characteristic of the terahertz wave in a mountain scene can be accurately predicted. The modeling method mainly comprises the steps of establishing a real mountain scene three-dimensional model, simulating to obtain channel model parameters, analyzing the statistical characteristics and performance of a communication channel, updating scene parameters to generate a new channel model and the like. The modeling method provided by the invention has the main thought that a channel model for accurately describing the channel characteristics is provided through a large amount of channel simulation data and channel characteristic analysis, and the channel statistical characteristics and the communication system performance are accurately described through adjusting scene parameters. A design proposal is provided for realizing reliable communication of the terahertz frequency band in the outdoor mountain scene.
Description
Technical Field
The invention relates to an unmanned aerial vehicle mountain terahertz channel modeling method based on ray tracing, and belongs to the technical field of terahertz communication.
Background
In recent years, the unmanned aerial vehicle has a wide application range in the field of wireless communication by virtue of the characteristics of low cost, high flexibility and the like. In some emergency and auxiliary mountain communication scenes, the unmanned aerial vehicle is used as an aerial base station, and a wireless communication network can be quickly and flexibly established, so that reliable information transmission is ensured.
Terahertz waves have the advantages of high frequency, narrow beam, large bandwidth, large channel capacity and the like. Terahertz channel modeling is mainly divided into the following three methods: deterministic channel modeling, semi-deterministic channel modeling, stochastic channel modeling. The method applies deterministic channel modeling, firstly establishes a 3D deterministic unmanned aerial vehicle mountain land model, then places a transmitter and a receiver at proper positions according to specific terrain, material characteristics, atmospheric environment and the like, and finally predicts a transmission model of a channel. The method for establishing the deterministic channel model comprises a ray tracing algorithm and a time domain finite difference method, and the method is mainly based on the modeling of the ray tracing algorithm. The ray tracing method applying the deterministic channel modeling can accurately predict the characteristic parameters of the channel, such as propagation path loss, time delay and the like.
However, currently, research on terahertz channels mostly focuses on indoor wireless channel transmission and outdoor short-distance communication, and a terahertz frequency band outdoor mountain wireless communication scene is not deeply analyzed. The existing research on terahertz outdoor communication channels generally focuses on analyzing channel characteristics of a cell or an urban scene, few researches on emergency communication scenes such as mountainous areas or suburbs are conducted, frequency bands are mainly focused on microwaves and millimeter waves, the terahertz frequency bands are not deeply researched, and meanwhile, experimental data are not sufficient.
Disclosure of Invention
The invention aims to solve the technical problem of providing an unmanned aerial vehicle mountain terahertz channel modeling method based on ray tracing, and aims to solve the problem.
The technical scheme of the invention is as follows: an unmanned aerial vehicle mountain terahertz channel modeling method based on ray tracing comprises the following specific steps:
step 1: establishing a real mountain scene three-dimensional model, and setting initial environment parameters, wherein the environment parameters comprise carrier frequency, transceiving distance, transmitting power, frequency bandwidth, antenna angle and the like;
step 2: according to the set environmental parameters, all paths from the transmitting end to the receiving end are tracked by rays, channel model parameters such as path loss, receiving power, time delay, arrival angle and the like are given in a simulation mode, and a signal intensity distribution diagram of a terrain area where the user terminal is located is generated;
step 3: obtaining channel statistical characteristics such as time delay expansion, molecular absorption loss, complex impulse response, channel H matrix and the like according to the channel model parameters;
step 4: analyzing the statistical characteristics of the channel, developing researches on bit error rate, throughput and the like, and evaluating the performance of the communication system in the scene;
step 5: adjusting scene parameters, returning to the step S1 by changing a modulation mode, atmospheric environment parameters and the vertical and horizontal positions of the unmanned aerial vehicle, generating a new channel model, and analyzing channel characteristics;
optionally, the outdoor mountain scene and scene parameters include a terrain size, a position distribution of the transmitter and the receiver, and the unmanned aerial vehicle, and a terahertz wave frequency.
Optionally, the mountain three-dimensional model is established, digital elevation Data (DEM) of an actual mountain scene is downloaded from a remote sensing data website such as USGS, and then post-processing work such as editing or capturing is performed by using corresponding GIS software. The scene initial parameters comprise terahertz wave center frequency, frequency bandwidth, antenna parameters, transmitters, receivers, unmanned aerial vehicle position distribution and the like. For a transmitting point and a receiving point, corresponding carrier waveforms and antennas need to be configured, the unmanned aerial vehicle is suspended on the ground at a certain height and used as an aerial base station, the user terminal is used as the receiving point and attached to the surface of an undulating terrain at a certain interval for simulation calculation, and propagation paths from all transmitting ends to a receiving end are traced by rays to obtain channel parameters of each propagation channel.
Optionally, the received power is in a free space with an antenna pattern, and the expression is as follows:
in the formula, P T Is the time-averaged radiation power, theta D And phi D Giving the direction of the ray leaving the transmitter, theta A And phi A The direction of the ray to the receiver is given and R represents the distance between the transmitter and the receiver. The received power in dBm is represented by:
P R (dBm)＝10log 10 [P R (W)]+30eB-L S (dB)
optionally, the path loss is a loss of energy power when propagating from the transmitting end to the receiving end. When the transmitting and receiving antenna is not an ideal isotropic antenna, the antenna has respective gains, and the gain of the transmitting antenna is G T Gain of receiving antenna is G R The path loss is:
L Path (dB)
＝P T (dBm)-P R (dBm)+G T,Max (dBi)+G R,Max (dBi)-L S (dB)
in the formula, G TMax Maximum gain of the transmitting antenna, G RMax For maximum gain of the receiving antenna, L S Represents the sum of all other losses in the system, including the bandwidth overlap factor. For directional antennas, the path loss depends on the direction of the antenna, and omni-directional antennas depend only on frequency and environment. In terahertz communication in general, a directional antenna is generally used to compensate for high propagation loss.
Optionally, the free space propagation loss is energy loss when terahertz propagates in air, and terahertz penetrates through a mediumThere will be a loss, the terahertz free space loss L FS Can be expressed as:
in the formula, G T Is the gain of the transmitting antenna, G R Is the gain of the receiving antenna and R is the distance between the transmitter and the receiver.
The molecular absorption loss is a frequency-dependent absorption effect of water vapor and oxygen molecular content in the atmosphere on the terahertz waves, the pressure, temperature and humidity in the atmospheric environment directly influence the size of the terahertz waves, the path loss and the receiving power are calculated according to the propagation distance, the frequency and the atmospheric conditions of light, and the molecular absorption loss L of the terahertz wave band caused by the oxygen and the water vapor in the atmosphere air Can be expressed as:
in the formula, gamma 0 Is the attenuation rate of oxygen in the atmosphere, gamma w Is the attenuation rate of water vapor, h 0 To dry the effective height of the air, h w And theta is the effective height of the water vapor, and theta is the communication elevation angle.
Optionally, the impulse response is that the transmitted signal is an impulse signal, and the impulse response of the channel is equivalent to the superposition of each path at the receiving antenna through multipath propagation:
optionally, the power delay profile describes the spread of the channel in time delay, and is an important parameter for characterizing a multipath fading channel. The time of the channel reaching the receiving end through different paths is different, which causes time dispersion. The power delay profile PDP can be expressed as the square of the channel impulse response:
φ(τ)＝|h(τ)| 2 ＝|h LoS (τ)| 2 +|h SB (τ)| 2 +|h DB (τ)| 2
optionally, the channel delay spread is due to multipath influence, the arrival time is spread in the time domain, and the average delay μ is τ And root mean square delay spread (RMS) σ τ It can be used to describe the delay spread of a channel, which can be calculated by a power delay profile PDP, and is expressed as:
in the formula u τ To average time delay, σ τ For root mean square delay spread, φ (τ) is the channel impulse response.
Optionally, the calculating of the bit error rate is to obtain a signal to noise ratio (SINR) by setting a power density and a signal bandwidth of the environmental noise, and further use the SINR and the BER as well as the throughput to calculate. The bit error rate is calculated according to an Additive White Gaussian Noise (AWGN) model, which applies the expression of BER in the presence of AWGN, without considering any dispersive effects of the channel, as:
in the formula, P R Is the received power, P I Is the power of the interference source, N 0 Is the power of the noise source.
Optionally, the modulation scheme supported by AWGN analysis includes PAM, QAM, PSK, DPSK, FSK, MSK, QPSK, etc., and the modulation scheme often determines the performance of the communication system, and in the case of QPSK modulation and AWGN channel, the calculation scheme of the bit error rate is:
optionally, the throughput is calculated by obtaining the output power of the receiver after ray tracing the propagation path of the electromagnetic wave from the transmitter to the receiver, and analyzing the transmitter providing the highest SINR for the position of each receiver in the scene, where each system selects a Modulation and Coding Scheme (MCS) according to a wireless communication access method, and the selected MCS is also directly related to the throughput of the channel. Since the signal bandwidth of several communication protocols is only 160MHz at the most, a self-defined communication protocol is used in the present invention, and the signal bandwidth is 10 GHz.
Optionally, the throughput analysis may be performed based on a communication protocol and a technology that applies beamforming, when the communication system includes TX/RX using MIMO antennas. The MRT technology is used in beam forming, the weight is calculated based on a channel matrix, an optimized beam is generated, a receiving end has the optimal receiving power, in an environment with obvious multipath effect influence, a plurality of lobes can be generated instead of the beam pointing to a single direction, if the receiving end is also an antenna array, optimization is carried out on a first antenna unit of the antenna array of the receiving end, and then gain is optimized by using other antenna units through the antenna diversity technology of the receiving end.
Optionally, the channel characteristics are generated, a modulation mode is changed by adjusting basic parameters of a scene, the modulation mode may be specifically set to PAM, QAM, PSK, DPSK, FSK, MSK, and influences on channel path loss, channel capacity, error rate, and the like under a line-of-sight condition are studied. The numerical values of temperature, humidity and pressure in the atmospheric environment are changed, on one hand, analysis can be performed from the perspective of a single environmental parameter, on the other hand, weather conditions of the plateau mountain environment can be integrally simulated, and the influence of the plateau mountain environment on terahertz wave propagation is analyzed. The position of the unmanned aerial vehicle in the vertical and horizontal directions is adjusted, the influence of the position change of the unmanned aerial vehicle on a channel can be researched, an unmanned aerial vehicle position point enabling the communication performance of a user terminal to be optimal is found, a new channel model is generated along with the change of scene parameters, and the influence on the terahertz wave channel propagation characteristic is analyzed.
The beneficial effects of the invention are: the method can acquire information such as all propagation paths, antenna angles, receiving power and the like of the terahertz waves in the process of propagating from the transmitting end to the receiving end, and channel model parameters required by channel modeling such as path loss, receiving power, time delay expansion and the like of terahertz mountain communication are obtained. And analyzing the performance of the communication system such as the error rate, the channel capacity and the like according to the simulated output channel H matrix, the complex impulse response and the like. More importantly, on the basis of the formed complete terahertz mountain land channel modeling, the model variables are changed again, the influence of the plateau mountain land environment, the modulation mode and the unmanned aerial vehicle position on the channel characteristics is researched, the channel model parameter can be adjusted to be suitable for multiple frequency bands and multiple scenes, the universality is good, the introduced scene models are all actual mountain land terrains, certain practicability is achieved for plateau regions of multiple mountains, the complexity is low, the implementation is easy, and the terahertz frequency band outdoor mountain land communication system has guiding significance in the design aspect.
Drawings
FIG. 1 is a schematic flow chart of a modeling method of a mountain terahertz communication channel of an unmanned aerial vehicle;
FIG. 2 is a simulation diagram of a mountain three-dimensional scene model of an unmanned aerial vehicle according to the invention;
fig. 3 is a three-dimensional plot of the received power of a stationary drone of the present invention for a particular mountain area;
FIG. 4 is a graph of a comparison of the received power of a fixed drone of the present invention for a standard atmospheric environment and a plateau mountain environment in a particular mountain area;
FIG. 5 is a comparison graph of error rates of a standard atmospheric pressure environment and a plateau mountain environment of a fixed unmanned aerial vehicle in a specific mountain area;
fig. 6 is a data plot of channel capacity for a particular mountain area for a fixed drone of the present invention;
fig. 7 is a graph of path loss data for a terminal when the drone of different altitudes flies at a particular trajectory according to the present invention;
fig. 8 is a diagram of the bit error rate data of the unmanned aerial vehicles with different heights for a terminal when flying in a specific track;
fig. 9 is a graph of bit error rate versus data for different modulation schemes of the present invention.
Detailed Description
The invention is further described with reference to the following drawings and detailed description.
At present, researches on terahertz channels are mostly concentrated on outdoor short-distance communication and indoor wireless channel transmission, mountain scene terahertz channels are involved in a geometric randomness channel modeling method, however, plateau mountain scene certainty modeling of terahertz frequency bands is not deeply analyzed; due to complex situations such as the fluctuation of mountain terrain and vegetation coverage, the influence of shielding on signals is difficult to eliminate in traditional communication, and an unmanned aerial vehicle can flexibly and three-dimensionally move in free space and can easily move from one place to another to provide on-demand communication support, the position of the unmanned aerial vehicle can be changed to avoid blockage/shadow, data relay/transmission application can be facilitated, the experience quality of a wireless user can be improved, and the communication requirement of a first responder at the most needed time/place can be supported. The use of unmanned planes has a great application prospect for terahertz communication to maintain the data rate requirements of high throughput mobile applications. In particular, the drone can maintain a line of sight (LOS) connection to the desired user by hovering in an advantageous location, which is critical to maintaining good link quality in the terahertz band. The influence of the horizontal position and the height position of the unmanned aerial vehicle on the channel is a key research problem. In addition, influences brought by atmospheric molecule absorption, free space propagation loss and the like are also considered, channel parameters can also be changed due to different modulation modes, and based on the comprehensive consideration, the mountain terahertz channel modeling method based on the unmanned aerial vehicle base station is designed, a system flow of channel modeling is established, a series of data such as channel model parameters, channel statistical characteristics and channel communication system performance are calculated in a simulation mode, and the performance of a channel model is analyzed according to a complex nonlinear mapping relation among the three data. Most importantly, the channel research of the multi-frequency band multi-model is realized by adjusting the parameters of the scene, and the universality is better. Corresponding design suggestions are provided for realizing future unmanned aerial vehicle mountain land scene air-ground terahertz reliable communication.
The method comprises the steps of establishing a real mountain scene three-dimensional model, simulating to obtain channel model parameters, analyzing the statistical characteristics and performance of a communication channel, updating scene parameters to generate a new channel model and the like.
As shown in fig. 1, a ray tracing-based modeling method for a terahertz channel of an unmanned aerial vehicle mountain land comprises the following specific steps:
step 1: and establishing a simulation model according to the three-dimensional terrain of the mountainous region and the scene parameters.
The mountain scene and scene parameters include, by way of example, terrain dimensions, mountain surface material, terahertz wave frequencies, antenna angles, and the like. The size of the terrain is about 5 kilometers multiplied by 5 kilometers, the highest height of the terrain is about 300 meters, when the terrain is guided into the terrain, the surface material of the mountainous region is set to be rock, and all materials have determined conductivity and dielectric constant and are also important parameters influencing the propagation of electromagnetic waves. The carrier frequency is set to be a terahertz frequency band of 110GHz, and after modeling simulation is completed according to a design flow, the carrier frequency value can be changed, and the characteristics of different terahertz wave bands in propagation of mountain scene channels are compared. The antenna has the maximum gain direction, and the angle of the antenna needs to be adjusted to be aligned to the direction of the receiving end, so that the propagation loss is reduced.
Step 2: the method comprises the steps of determining the positions of a terahertz wave transmitter and a terahertz wave receiver, in order to research the communication performance of a user terminal in a specific mountain region, enabling an unmanned aerial vehicle to be used as an aerial base station to suspend at a certain height of the mountain region to assist communication, enabling the user receiver to be paved in the specific mountain region at a certain interval distance, tracing the sight distance paths from all the transmitters to the receiver by rays, giving channel model parameters such as path loss, receiving power, time delay and arrival angle through simulation, and generating a topographic region surface signal intensity distribution diagram. In another mode, the user terminal is placed in the mountain as a transmitter, and the unmanned aerial vehicle is used as a receiver, so that a 100-meter receiver straight path is formed at a distance of 1 meter interval in the horizontal direction. The flying speed of the unmanned aerial vehicle is set to be 1m/s, the flying speed is sequentially adjusted to be 20m, 30m, 40m and 50m in height, and the channel characteristics of the unmanned aerial vehicle at different positions are simulated.
In the embodiment of the invention, because the mountain scene emergency communication is adopted and the terahertz wave is transmitted, only the short-distance line-of-sight communication between the user and the unmanned aerial vehicle is considered, so that the unmanned aerial vehicle is ensured to appear at a proper position and is not shielded from the user. And (4) simulating and calculating relevant channel parameters of the line-of-sight path.
Terahertz is lossy when penetrating any medium, and terahertz free space is lossy FS Can be expressed as:
wherein G is T Is the gain of the transmitting antenna in the direction of the receiver, G R Is the gain of the receiving antenna in the direction of the transmitter and R is the distance between the transmitter and the receiver.
Step 3: and according to the simulated channel model parameters, giving channel characteristic data such as time delay expansion, complex impulse response, molecular absorption loss and the like, and if the antennas used by the transmitting end and the receiving end are MIMO array antennas, deriving a channel H matrix data file.
The channel matrix, commonly referred to as the H-matrix, of a MIMO system is a matrix that defines the complex channel gains between the antenna elements in the transmitter and the antenna elements in the receiver. Its dimension is N t ×N r In which N is t Number of transmitting antennas, N r Is the number of receive antennas. Each value in the matrix is a complex number that represents the magnitude and phase of the channel gain between a pair of transmit and receive antenna elements. The h-matrix has a different definition depending on how the h-matrix is normalized and whether each element represents a channel gain or a complex conjugate of a channel gain. The signal at the receiver is calculated as:
y＝Hx+n
where x is an Nt × 1 vector containing the transmission signal, y is an Nr × 1 vector containing the reception signal, N is a noise vector, and H is an N of the complex channel gain t ×N r Matrix as the amount of voltage. Sometimes the matrix is reduced to a one-dimensional vector, designated with a lower case h. This is used to assume that a single antenna is on one side of the system, or when the contributions of multiple antennas are combined, for example in the case of receiver diversity techniques, only the total number of each receiver element is considered.
The molecular absorption loss is a special absorption effect of water molecules and oxygen molecules in the atmosphere on the terahertz waveband, so that the refractive index of the atmosphere in the terahertz waveband becomes a negative refractive index, the specific value of the refractive index is determined by the pressure, the temperature and the humidity under different atmospheric environments, and the molecular absorption loss L of the oxygen and the water vapor in the atmosphere on the terahertz waveband is ai·r Can be expressed as:
wherein, γ 0 Attenuation rate, gamma, caused by atmospheric oxygen w Attenuation rate due to water vapor, h 0 To dry the effective height of the air, h w And theta is the effective height of the water vapor and the communication elevation angle.
The impulse response is that the transmitted signal is delta (t) impulse, and the channel impulse response synthesized by each path at the receiving antenna is as follows:
wherein N is the number of multipaths, a n Representing the multipath propagation attenuation factor, tau n In order to achieve a multi-path propagation delay,
is the multipath propagation phase.
In the embodiment of the invention, the power delay spectrum describes the diffusion of the channel in time delay and is an important parameter for characterizing a multipath fading channel. The time of the channel reaching the receiving end through different paths is different, which causes time dispersion. The power delay profile PDP can be expressed as the square of the channel impulse response:
φ(τ)＝|h(τ)| 2 ＝|h LoS (τ)| 2 +|h SB (τ)| 2 +|h DB (τ)| 2
the channel delay spread is due to the influence of multipath, and the arrival time is spread in the time domain and averagedDelay mu τ And root mean square delay spread (RMS) σ τ It can be used to describe the delay spread of a channel, which can be calculated by a power delay profile PDP, and is expressed as:
step 4: and analyzing the statistical characteristics of the channel, developing researches on the error rate, the throughput and the like, and evaluating the performance of the communication system in the scene.
In the embodiment of the invention, the bit error rate is calculated by setting the power density and the signal bandwidth of the environmental noise to obtain the signal to noise ratio (SINR), and further used for calculating the Bit Error Rate (BER) and the throughput. The bit error rate is calculated according to an Additive White Gaussian Noise (AWGN) model, which applies the expression of BER in the presence of AWGN, without considering any dispersive effects of the channel, as:
wherein, P R Is the received power, P I Is the power of the interference source, N 0 Is the power of the noise source.
Modulation schemes supported by AWGN analysis include PAM, QAM, PSK, DPSK, FSK, MSK, QPSK, etc., and the modulation schemes also often determine the performance of the communication system, and in the case of QPSK modulation and AWGN channel, the error rate is calculated by:
step 5: and returning to the step S1 by changing the modulation mode, the atmospheric environment parameters and the vertical and horizontal positions of the unmanned aerial vehicle, generating a new channel model, and analyzing the channel characteristics.
In Step5, the design scheme for changing the atmospheric environment parameters is as follows: the numerical values of temperature, humidity and pressure in the atmospheric environment are changed, on one hand, analysis can be performed from the perspective of a single environmental parameter, on the other hand, the weather condition of the plateau environment can be integrally simulated, and the influence of the plateau environment on terahertz wave propagation is analyzed. In this embodiment, the base station of the unmanned aerial vehicle is suspended 40 meters above the terrain as a transmitter, the user receivers cover a full square area with the side length of 100 meters, and the interval distance between each receiver is 5 meters, which is 400 in total. It can be seen from fig. 3 that the received power of the receiver which is fully paved in a specific area is between-65 to-125 dbm, which conforms to the normal range of the received power of the mobile phone terminal, the received power and the error rate in the standard atmospheric pressure environment and the plateau mountain atmospheric pressure environment are compared, and the standard atmospheric condition parameters are set as follows: temperature 22 deg.C, air pressure 1013mbar, and humidity 50%; the plateau mountain region condition parameters are set as follows: the temperature is 15 ℃, the air pressure is 807mbar, the humidity is 40%, the simulation result is shown in fig. 4 and fig. 5, and the comparison shows that the receiving power under the plateau mountain environment is generally greater than that under the standard atmospheric pressure environment, because the atmospheric pressure and the humidity are reduced along with the increase of the altitude of the plateau mountain, the oxygen and water molecule content in the atmosphere is reduced, the molecular absorption loss is reduced, and therefore the receiving power is higher than that under the standard atmospheric pressure environment. Fig. 5 shows that the error rate of the channels in the plateau mountain environment is generally smaller than that in the standard atmospheric environment according to the same analysis. FIG. 6 shows channel capacity in the range of 0-60Gbit/s for two atmospheric environments.
In Step5, the unmanned aerial vehicle position change design scheme is as follows: the user is as the transmitter, and unmanned aerial vehicle is as the receiver, forms a 100 meters moving route with 1 meter interval distance, and unmanned aerial vehicle flying speed is 1m/s, changes the height in route again, observes the position of the best unmanned aerial vehicle of communication performance. The channel path loss and bit error rate data result is simulated, as shown in fig. 7 and 8, it can be seen from fig. 7 that when the unmanned aerial vehicle starts to approach the user slowly along the path, the path loss is reduced slowly, between 48-52 meters, and when the unmanned aerial vehicle arrives right above the user transmitter, because the unmanned aerial vehicle base station carries the half-wave dipole antenna, the maximum gain of the antenna is along the horizontal direction of the X axis, the antenna gain at this moment is minimum, a salient point with increased loss appears in the data diagram, the unmanned aerial vehicle moves forward continuously, the distance from the user is farther and farther, and the path loss is increased slowly. And the path loss increases as the altitude of the drone increases. Fig. 8 shows a similar trend of the bit error rate and the received power. It is worth noting that in the 0-25 m and 75-100 m intervals, the height is low, but the path loss and the error rate are large, which is caused by the change of the alignment angle between the high gain direction of the antenna and the user antenna of the unmanned aerial vehicle in the intervals. By means of the result analysis, the position with the best communication performance between the unmanned aerial vehicle and the user can be found conveniently.
In Step5, the design scheme for changing the modulation mode is as follows: keeping the height position of the unmanned aerial vehicle unchanged, flying the unmanned aerial vehicle along a horizontal path at the height of 20 meters, setting the modulation modes to be DPSK, PAM, QAM, PSK, FSK and MSK respectively, as shown in FIG. 9, under the MSK modulation mode, the error rate of a channel is minimum, the communication performance is optimal, and the error rate of FSK is larger than that of other modulation modes.
The method mainly comprises the modeling processes of establishing a real mountain scene three-dimensional model, obtaining channel model parameters through simulation, analyzing the statistical characteristics and performance of a communication channel, updating scene parameters and generating a new channel model and the like. The antenna is applied to the practical situation, the set frequency can reach a terahertz frequency band, the antenna is more in selected types, and the antenna further comprises an MIMO array antenna. Obtaining some important channel model parameters through simulation analysis, obtaining a relation curve between the error rate and the transmission distance of a receiving system in a plateau environment by using a method of error rate theoretical analysis in different modulation modes such as QPSK and the like, wherein the error rate is gradually increased along with the increase of the transmission distance; under the mountain land environment of plateau, communication system is more reliable and more stable.
The invention provides a method for generating a step-by-step channel parameter, which can be configured according to actual conditions and can better simulate the characteristics of an actual mountain scene terahertz communication channel; the modeling method covers main parameter data of terahertz channel modeling, can change scene parameters to perform characteristic analysis of a dynamically updatable terahertz channel, and provides corresponding design suggestions for realizing reliable communication of future mountain scene terahertz.
While the present invention has been described in detail with reference to the embodiments shown in the drawings, the present invention is not limited to the embodiments, and various changes can be made without departing from the spirit and scope of the present invention.
Claims (7)
1. An unmanned aerial vehicle mountain terahertz channel modeling method based on ray tracing is characterized in that:
step 1: establishing a real mountain scene three-dimensional model, and setting initial environment parameters, wherein the environment parameters comprise carrier frequency, transceiving distance, transmitting power, frequency bandwidth and antenna angle;
step 2: according to the set environmental parameters, all paths from the transmitting end to the receiving end are tracked by rays, channel model parameters are given out in a simulation mode, and a signal intensity distribution diagram of a terrain area where the user terminal is located is generated; the channel model parameters comprise path loss, received power, time delay and arrival angle;
step 3: obtaining channel statistical characteristics including time delay expansion, molecular absorption loss, complex impulse response and a channel H matrix according to the channel model parameters;
step 4: analyzing the channel statistical characteristics, developing researches on the error rate and the throughput, and evaluating the performance of the communication system in the scene;
step 5: adjusting scene parameters, changing a modulation mode, atmospheric environment parameters and the vertical and horizontal positions of the unmanned aerial vehicle, returning to Step1, generating a new channel model, and analyzing channel characteristics.
2. The unmanned aerial vehicle mountain terahertz channel modeling method based on ray tracing as claimed in claim 1, wherein the establishing of the real mountain scene three-dimensional model specifically is: firstly, downloading digital elevation data of an actual mountain scene from a remote sensing data website, and then using corresponding GIS software to perform post-processing work such as editing or capturing and the like to complete model establishment; the scene initial parameters comprise terahertz wave center frequency, frequency bandwidth, antenna parameters, transmitters, receivers and unmanned aerial vehicle position distribution.
3. The unmanned aerial vehicle mountain terahertz channel modeling method based on ray tracing as claimed in claim 1, characterized in that: in Step2, the received power is the sum of the powers of the effective paths from the transmitting end to the receiving end, and in the free space with the antenna pattern, the expression is:
in the formula, P T Is the time-averaged radiation power, theta D And phi D In the direction of the rays leaving the transmitter, theta A And phi A R represents the distance between the transmitter and the receiver, which is the direction of the ray reaching the receiver;
the received power in dBm is expressed as:
P R (dBm)＝10log 10 [P R (W)]+30dB-L S (dB)。
4. the unmanned aerial vehicle mountain terahertz channel modeling method based on ray tracing as claimed in claim 1, characterized in that: in Step2, the path loss refers to the loss of energy power when propagating from the transmitting end to the receiving end, and the gain of the transmitting antenna is G T Gain of receiving antenna is G R The path loss is:
L Path (dB)
＝P T (dBm)-P R (dBm)+G T,Max (dBi)+G R,Max (dBi)-L S (dB)
in the formula, G TMax For maximum gain of the transmitting antenna, G RMax For maximum gain of the receiving antenna, L S Represents the sum of all other losses in the system, including the bandwidth overlap factor.
5. The unmanned aerial vehicle mountain terahertz channel modeling method based on ray tracing as claimed in claim 1, characterized in that: in Step3, the molecular absorption loss refers to the frequency-dependent absorption effect of the content of water vapor and oxygen molecules in the atmosphere on the terahertz waves, and the oxygen vapor and the water vapor in the atmosphere on the terahertz wavesMolecular absorption loss L of band air Expressed as:
in the formula, gamma 0 Is the propagation attenuation rate of oxygen in the atmosphere, gamma w Is the propagation attenuation rate of water vapor, h 0 To dry the effective height of the air, h w And theta is the effective height of the water vapor and the communication elevation angle.
6. The unmanned aerial vehicle mountain terahertz channel modeling method based on ray tracing as claimed in claim 1, characterized in that: in Step3, the complex impulse response means that the transmitted signal is an impulse signal and is propagated through multiple paths, and the channel impulse response is equivalent to the superposition of paths at the receiving antenna and is represented as:
wherein N is the number of multipaths, a n Representing the multipath propagation attenuation factor, tau n In order to achieve a multi-path propagation delay,
is the multipath propagation phase.
7. The unmanned aerial vehicle mountain terahertz channel modeling method based on ray tracing as claimed in claim 1, characterized in that: in Step4, the bit error rate is calculated by setting the power density and signal bandwidth of the environmental noise to obtain the signal-to-noise ratio, and further used for calculating the bit error rate and the throughput:
SNR(dB)＝10log 10 (P R (i))-10log 10 (N total )
wherein, P R Is the power received from the transmitter, N total Is the sum of noise, and the error rate is calculated based on white additive Gaussian noiseThe model, abbreviated AWGN, applies the expression of BER in the presence of AWGN without considering any dispersive effects of the channel:
wherein, P R Is the received power, P I Is the power of the interference source, N 0 Is the power of the noise source.
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