CN115085839B - 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 PDF

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CN115085839B
CN115085839B CN202210660734.7A CN202210660734A CN115085839B CN 115085839 B CN115085839 B CN 115085839B CN 202210660734 A CN202210660734 A CN 202210660734A CN 115085839 B CN115085839 B CN 115085839B
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channel
mountain
terahertz
parameters
scene
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CN115085839A (en
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宋健
丁鹏辉
沈韬
王青旺
陈金江
李宏伟
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Kunming University of Science and Technology
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B17/00—Monitoring; Testing
    • H04B17/30—Monitoring; Testing of propagation channels
    • H04B17/391—Modelling the propagation channel
    • H04B17/3912—Simulation models, e.g. distribution of spectral power density or received signal strength indicator [RSSI] for a given geographic region
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B1/00—Details of transmission systems, not covered by a single one of groups H04B3/00 - H04B13/00; Details of transmission systems not characterised by the medium used for transmission
    • H04B1/38—Transceivers, i.e. devices in which transmitter and receiver form a structural unit and in which at least one part is used for functions of transmitting and receiving
    • H04B1/3822—Transceivers, i.e. devices in which transmitter and receiver form a structural unit and in which at least one part is used for functions of transmitting and receiving specially adapted for use in vehicles
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B10/00—Transmission systems employing electromagnetic waves other than radio-waves, e.g. infrared, visible or ultraviolet light, or employing corpuscular radiation, e.g. quantum communication
    • H04B10/90—Non-optical transmission systems, e.g. transmission systems employing non-photonic corpuscular radiation
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B17/00—Monitoring; Testing
    • H04B17/30—Monitoring; Testing of propagation channels
    • H04B17/309—Measuring or estimating channel quality parameters
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B17/00—Monitoring; Testing
    • H04B17/30—Monitoring; Testing of propagation channels
    • H04B17/309—Measuring or estimating channel quality parameters
    • H04B17/318—Received signal strength
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
    • Y02D30/00—Reducing energy consumption in communication networks
    • Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks

Abstract

The invention relates to an unmanned aerial vehicle mountain land terahertz channel modeling method based on ray tracing, and belongs to the technical field of terahertz communication. According to the invention, the propagation path of the electromagnetic wave is tracked by a ray tracing method, so that the propagation characteristic of the terahertz wave in a mountain scene can be accurately predicted. The modeling method mainly comprises the steps of building a three-dimensional model of a real mountain scene, obtaining channel model parameters through simulation, analyzing the statistical characteristics and performance of a communication channel, updating the scene parameters to generate a new channel model and the like. The modeling method provided by the invention mainly aims at providing a channel model for accurately describing the channel characteristics through a large amount of channel simulation data and channel characteristic analysis, and accurately describing the channel statistical characteristics and the communication system performance through adjusting scene parameters. Design suggestions are provided for realizing reliable communication of terahertz frequency bands of outdoor mountain scenes.

Description

Unmanned aerial vehicle mountain terahertz channel modeling method based on ray tracing
Technical Field
The invention relates to an unmanned aerial vehicle mountain land terahertz channel modeling method based on ray tracing, and belongs to the technical field of terahertz communication.
Background
In recent years, unmanned aerial vehicles have a wide application range in the field of wireless communication due to the characteristics of low cost, high flexibility and the like. In some emergency and auxiliary mountain communication scenarios, a wireless communication network can be quickly and flexibly established by using an unmanned aerial vehicle as an air base station, so that reliable transmission of information 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 invention uses deterministic channel modeling, firstly establishes a 3D deterministic unmanned aerial vehicle mountain model, then places a transmitter and a receiver at a proper position according to specific topography, material characteristics, atmospheric environment and the like, and finally predicts a transmission model of a channel. The establishment method of the deterministic channel model comprises a ray tracing algorithm and a time domain finite difference method, and the method is mainly based on modeling of the ray tracing algorithm. The ray tracing method using deterministic channel modeling can accurately predict channel characteristic parameters such as propagation path loss, time delay and the like.
However, in the current research on terahertz channels, most of the research is focused on indoor wireless channel transmission and outdoor short-distance communication, and no deep analysis is made on the outdoor mountain wireless communication scene of the terahertz frequency band. The existing research on the terahertz outdoor communication channel generally analyzes the channel characteristics of a district or city scene in a centralized manner, the research on emergency communication scenes such as mountain areas or suburbs is less, the frequency band is mainly concentrated on microwaves and millimeter waves, the research on the terahertz frequency band is not deep enough, and meanwhile, experimental data is also insufficient.
Disclosure of Invention
The invention aims to provide a method for modeling a mountain terahertz channel of an unmanned aerial vehicle based on ray tracing, which is used for solving the problems.
The technical scheme of the invention is as follows: a modeling method of an unmanned aerial vehicle mountain terahertz channel based on ray tracing comprises the following specific steps:
step1: establishing a real mountain scene three-dimensional model, and setting initial environmental parameters including carrier frequency, receiving and transmitting distance, transmitting power, frequency bandwidth, antenna angle and the like;
step2: according to the set environmental parameters, the rays trace all paths from the transmitting end to the receiving end, channel model parameters such as path loss, receiving power, time delay, arrival angle and the like are given through simulation, and a signal intensity distribution map of a terrain area where the user terminal is located is generated;
step3: obtaining channel statistical characteristics such as delay spread, molecular absorption loss, complex impulse response, channel H matrix and the like according to the channel model parameters;
step4: analyzing channel statistical characteristics, developing and researching bit error rate, throughput and the like, and evaluating the performance of a scene communication system;
step5: adjusting scene parameters, 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 to generate a new channel model and analyzing the channel characteristics;
optionally, the outdoor mountain scene and scene parameters include a terrain size, a position distribution of a transmitter and a receiver and the unmanned aerial vehicle, and terahertz wave frequency.
Optionally, the three-dimensional mountain model is built by downloading digital elevation Data (DEM) of the actual mountain scene from remote sensing data websites such as USGS, and then performing post-processing such as editing or capturing by using corresponding GIS software. The scene initial parameters comprise terahertz wave center frequency, frequency bandwidth, antenna parameters, position distribution of a transmitter and a receiver, a unmanned aerial vehicle and the like. For a transmitting point and a receiving point, corresponding carrier waveforms and antennas are required to be configured, the unmanned aerial vehicle is suspended on the ground at a certain height and used as an air base station, a user terminal is used as the receiving point and is attached to the surface of the undulating terrain at a certain interval distance for simulation calculation, and the propagation paths from all transmitting ends to the receiving ends are tracked by rays to obtain the channel parameters of each propagation channel.
Optionally, the received power is expressed in free space with antenna mode as:
wherein P is T For time-averaged radiation power, θ D And phi D Gives the direction of the ray leaving the transmitter, θ A And phi A The direction of the ray reaching the receiver is given, and R represents the distance from the transmitter to the receiver. The received power in dBm is represented by the following formula:
P R (dBm)＝10log 10 [P R (W)]+30eB-L S (dB)
alternatively, the path loss is the loss of energy power when propagating from the transmitting end to the receiving end. When the receiving and transmitting antenna is not an ideal isotropic antenna, the receiving antenna has respective gains, and the gain of the transmitting antenna is G T The gain of the 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)
wherein G is TMax G for maximum gain of transmitting antenna RMax For maximum gain of the receiving antenna, L S Representing 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, while omni-directional antennas depend only on frequency and environment. Typically in terahertz communications, directional antennas are often used to compensate for high propagation losses.
Optionally, the free space propagation loss is energy loss when terahertz propagates in air, and terahertz has loss when the terahertz penetrates through a medium, so that terahertz free space loss L FS Can be expressed as:
wherein G is 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 the frequency-dependent absorption effect of the content of water vapor and oxygen molecules in the atmosphere on terahertz waves, the pressure, the temperature and the humidity in the atmosphere 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 atmosphere condition of light, and the molecular absorption loss L of the oxygen and the water vapor in the atmosphere on the terahertz wave band air Can be expressed as:
wherein, 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 θ is the communication elevation angle, which is the effective height of the water vapor.
Optionally, the impulse response is that the transmitted signal is a pulse signal, and the channel impulse response corresponds to superposition of paths at the receiving antenna through multipath propagation:
optionally, the power delay profile describes the spread of the channel over time delay, and is an important parameter characterizing a multipath fading channel. The time that the channel reaches the receiving end through different paths is different, so that the time is diffused. The power delay profile PDP may 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 effects, the arrival time is spread in the time domain, and the average delay μ τ And root mean square delay spread (RMS) sigma τ The delay spread that can be used to describe the channel can be calculated by the power delay profile PDP, expressed as:
wherein u is τ For average time delay, sigma τ For root mean square delay spread, phi (tau) is the channel impulse response.
Optionally, the calculating of the bit error rate is to calculate a signal to noise ratio (SINR) by setting a power density and a signal bandwidth of the environmental noise, and further use the calculated Bit Error Rate (BER) and throughput. The bit error rate is calculated according to an Additive White Gaussian Noise (AWGN) model, and the expression of BER when AWGN exists is applied under the condition that no dispersion effect of a channel is considered:
wherein P is 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 modes supported by the AWGN analysis include PAM, QAM, PSK, DPSK, FSK, MSK, QPSK, and the modulation modes often determine the performance of the communication system, and in the case of QPSK modulation and AWGN channel, the calculation modes of the error rate are:
optionally, the calculation of throughput is to obtain the output power of the receiver after the radiation tracking of the propagation path of the electromagnetic wave from the transmitter to the receiver, and for the position of each receiver in the scene, analyze the transmitter providing the highest SINR, each system will select a Modulation and Coding Scheme (MCS) according to the 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 160MHz at the highest, the communication protocol defined by the user is used in the invention, and the signal bandwidth is 10GHz.
Alternatively, the analysis of throughput may be performed when the communication system includes TX/RX using MIMO antennas, and throughput analysis based on a communication protocol and using beamforming techniques or the like. In beam forming, an MRT technology is used, weights are calculated based on a channel matrix, an optimized beam is generated, the receiving end has optimal receiving power, multiple lobes can be generated instead of beams pointing to a single direction under the condition that a multipath effect affects obviously, if the receiving end is also an antenna array, the first antenna unit of the antenna array of the receiving end is optimized, and then the antenna diversity technology of the receiving end is used for optimizing the gain by using other antenna units.
Optionally, the generating the channel characteristic changes the modulation mode by adjusting the basic parameters of the scene, and the modulation mode may be set to PAM, QAM, PSK, DPSK, FSK, MSK specifically, so as to study the influence on the channel path loss, the channel capacity, the bit error rate and the like under the line-of-sight condition. The values of temperature, humidity and pressure in the atmosphere environment are changed, so that on one hand, analysis can be performed from the perspective of single environment parameters, on the other hand, the weather conditions of the mountain land can be integrally simulated, and the influence of the mountain land environment on the transmission of terahertz waves can be analyzed. The position of the unmanned aerial vehicle in the vertical direction and the horizontal direction is adjusted, the influence of the position change of the unmanned aerial vehicle on a channel can be studied, the unmanned aerial vehicle position point which enables the communication performance of the 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 characteristics is analyzed.
The beneficial effects of the invention are as follows: the invention can acquire all information such as propagation paths, antenna angles, receiving power and the like of the terahertz waves in the process of propagation from the transmitting end to the receiving end, and obtains channel model parameters required by channel modeling such as path loss, receiving power, time delay expansion and the like of terahertz mountain communication. And analyzing the performance of the communication system such as error rate, channel capacity and the like according to the simulated output channel H matrix, complex impulse response and the like. More importantly, on the basis of the formed complete terahertz mountain channel modeling, model variables are changed again, influences of mountain environments, modulation modes and unmanned aerial vehicle positions on channel characteristics are researched, the method can be applicable to multiple frequency bands and multiple scenes through adjustment of channel model parameters, the universality is good, the imported scene models are all actual mountain terrains, certain practicability is achieved for mountain areas of multiple mountain areas, the complexity is low, implementation is easy, and the method has guiding significance in the aspect of design of terahertz frequency band outdoor mountain communication systems.
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 three-dimensional scene model of an unmanned aerial vehicle mountain land according to the present invention;
FIG. 3 is a three-dimensional plot of received power of the stationary drone of the present invention for a particular mountain area;
FIG. 4 is a graph of the received power of a stationary unmanned aerial vehicle versus standard atmospheric environment and a plateau mountain environment for a particular mountain area of the present invention;
FIG. 5 is a graph showing the comparison of the error rates of a standard atmospheric pressure environment and a plateau mountain environment of a specific mountain area by a fixed unmanned aerial vehicle;
FIG. 6 is a graph of channel capacity data for a stationary drone of the present invention for a particular mountain area;
FIG. 7 is a graph of path loss data for a terminal for different altitudes of the present invention when flying on a particular trajectory;
FIG. 8 is a bit error rate data graph of the unmanned aerial vehicle with different heights for a terminal when flying on 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 will be further described with reference to the drawings and detailed description.
At present, the research on terahertz channels is mostly focused on outdoor short-distance communication and indoor wireless channel transmission, the terahertz channels of mountain scenes are involved in a geometric stochastic channel modeling method, but the deterministic modeling of the mountain scenes of the terahertz frequency band plateau has not been deeply analyzed; due to the complex situation of relief of mountain terrain and vegetation coverage, traditional communications have difficulty in eliminating the effect of occlusion on signals, while unmanned aerial vehicles move flexibly and three-dimensionally in free space, can easily move from place to provide on-demand communication support, can change their position to avoid blockage/shadowing, can help data relay/transmission applications, helps improve the quality of experience of wireless users, and supports the communication needs of first responders at the most needed time/place. The use of unmanned aerial vehicles has a very large application prospect for terahertz communication to maintain the data rate requirements of high-throughput mobile applications. In particular, the drone can maintain line of sight (LOS) connection with 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 an important research problem. In addition, the influence caused by atmospheric molecular absorption, free space propagation loss and the like is also considered, the channel parameters are also changed due to different modulation modes, based on the comprehensive consideration, the invention designs a mountain terahertz channel modeling method based on an unmanned aerial vehicle base station, a channel modeling system flow is established, a series of data such as channel model parameters, channel statistics characteristics, channel communication system performance and the like are calculated through simulation, and the performance of a channel model is analyzed according to a complex nonlinear mapping relation among the three. Most importantly, the channel research on the multi-band multi-model is realized by adjusting the parameters of the scene, so that the method has better universality. The method provides corresponding design suggestions for realizing space-ground terahertz reliable communication of the mountain scene of the unmanned aerial vehicle in the future.
The method comprises the steps of building a three-dimensional model of a real mountain scene, obtaining channel model parameters through simulation, analyzing the statistical properties and performances of a communication channel, updating the scene parameters to generate a new channel model and the like.
As shown in fig. 1, an unmanned aerial vehicle mountain terahertz channel modeling method based on ray tracing specifically includes the steps:
step1: and establishing a simulation model according to the three-dimensional terrain and the scene parameters of the mountain land.
As examples, the mountain scene and scene parameters include terrain size, mountain surface material, terahertz wave frequency, antenna angle, etc. The landform is about 5 km by 5 km, the highest height of the landform is about 300 m, the mountain surface material is set as rock when the landform is introduced, and various materials have definite conductivity and dielectric constant and are also important parameters for influencing the propagation of electromagnetic waves. The carrier frequency is set to be a terahertz frequency band of 110GHz, after modeling simulation is completed according to a design flow, the carrier frequency value can be changed, and the characteristics of channel propagation of different terahertz wave bands in mountain scenes are compared. The antenna has the maximum gain direction, and the antenna angle is required to be adjusted to be aligned to the direction of the receiving end, so that the propagation loss is reduced.
Step2: the positions of terahertz wave transmitters and receivers are determined, in order to study the communication performance of a user terminal in a specific mountain region, an unmanned aerial vehicle is suspended at a certain mountain region height as an air base station to assist communication, the user receivers are paved in the specific region at a certain interval distance, the sight path from all transmitters to the receivers is tracked by rays, channel model parameters such as path loss, receiving power, time delay, arrival angle and the like are given through simulation, and a topography region surface signal intensity distribution map is generated. In another way, the user terminal is placed in the mountain as a transmitter and the unmanned aerial vehicle as a receiver forms a receiver straight line path of 100 meters at 1 meter spacing distance in the horizontal direction. The flying speed of the unmanned aerial vehicle is set to be 1m/s, and is sequentially adjusted to be 20m,30m,40m and 50m in height, so that the channel characteristics of the unmanned aerial vehicle at different positions are simulated.
In the embodiment of the invention, the mountain scene emergency communication is realized, and the terahertz wave propagation is realized, so that only the short-distance line-of-sight communication between the user and the unmanned aerial vehicle is considered, and the unmanned aerial vehicle is ensured to be in a proper position and is not shielded with the user. The simulation calculates the relevant channel parameters of the line-of-sight path.
Terahertz is lost when penetrating any medium, so that terahertz free space loss L FS Can be expressed as:
wherein G is T Is the gain of the transmitting antenna in the receiver direction, 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.
Step3: and according to the simulated channel model parameters, channel characteristic data such as time delay expansion, complex impulse response, molecular absorption loss and the like are given, and if antennas used by a transmitting end and a receiving end are MIMO array antennas, a channel H matrix data file can be derived.
The channel matrix of a MIMO system, commonly referred to as the H matrix, is a matrix that defines the complex channel gains between the antenna elements of the transmitter and the antenna elements in the receiver. It has dimension N t ×N r Wherein N is t For transmitting the antenna number N r Is the number of receiving antennas. Each value in the matrix is a complex number representing the magnitude and phase of the channel gain between a pair of transmit and receive antenna elements. The h-matrix is defined differently depending on how the h-matrix is normalized and whether each element represents a channel gain or a complex conjugate of the channel gain. The signal at the receiver is calculated as:
y＝Hx+n
where x is Nt×1 vector containing the transmission signal, y is Nr×1 vector containing the received signal, N is noise vector, and H is N of complex channel gain t ×N r A matrix as a voltage quantity. Sometimes the matrix is reduced to a one-dimensional vector, specified in lowercase h. This is used to assume that a single antenna is on one side of the system, or that only the total number of each receiver element is considered when the contributions of multiple antennas are combined, as is the case in receiver diversity techniques.
The molecular absorption loss is the special absorption effect of water molecules and oxygen molecules in the atmosphere on the terahertz wave band, so that the refractive index of the atmosphere in the terahertz wave band becomes a negative refractive index, the specific value is determined by the pressure, the temperature and the humidity in different atmospheric environments, and the molecular absorption loss L of oxygen and water vapor in the atmosphere on the terahertz wave band ai·r Can be expressed as:
wherein, gamma 0 Is the attenuation rate of oxygen in the atmosphere, gamma w Attenuation rate caused by water vapor, h 0 To dry the effective height of the air, h w And θ is the communication elevation angle, which is the effective height of the water vapor.
The impulse response is that the transmitted signal is delta (t) impulse, and after multipath propagation, the channel impulse response synthesized by each path at the receiving antenna is:
wherein N is the number of multipaths, a n Representing multipath propagation attenuation factor, τ n For the multipath propagation delay,is the multipath propagation phase.
In the embodiment of the invention, the power delay profile describes the spreading of the channel on the delay, and is an important parameter for representing a multipath fading channel. The time that the channel reaches the receiving end through different paths is different, so that the time is diffused. The power delay profile PDP may 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 multipath effect, the arrival time is spread in time domain, and the average delay mu τ And root mean square delay spread (RMS) sigma τ The delay spread that can be used to describe the channel can be calculated by the power delay profile PDP, expressed as:
step4: and analyzing the statistical characteristics of the channels, developing and researching bit error rate, throughput and the like, and evaluating the performance of the communication system in the scene.
In the embodiment of the invention, the calculation of the bit error rate is to calculate the signal to noise ratio (SINR) by setting the power density and the signal bandwidth of the environmental noise, and further to be used for the calculation of the Bit Error Rate (BER) and the throughput. The bit error rate is calculated according to an Additive White Gaussian Noise (AWGN) model, and the expression of BER when AWGN exists is applied under the condition that no dispersion effect of a channel is considered:
wherein P is R Is the received power, P I Is the power of the interference source, N 0 Is the power of the noise source.
The modulation schemes supported by AWGN analysis include PAM, QAM, PSK, DPSK, FSK, MSK, QPSK, etc., and often the modulation schemes also determine the performance of the communication system, and in the case of QPSK modulation and AWGN channel, the calculation schemes of the bit error rate are:
step5: and (3) 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 values of temperature, humidity and pressure in the atmosphere environment are changed, so that on one hand, analysis can be performed from the perspective of single environmental parameters, on the other hand, the weather conditions of the plateau environment can be integrally simulated, and the influence of the plateau environment on the transmission of terahertz waves can be analyzed. In this embodiment, the base station of the unmanned aerial vehicle is suspended as a transmitter at 40 meters above the terrain, and the user receivers cover a square area with a side length of 100 meters, and the distance between each two receivers is 5 meters, which is 400. As can be seen from fig. 3, the receiving power of the receiver spreading over the specific area is between-65 and-125 dbm, which accords with the normal range of the receiving power of the mobile phone terminal, and the receiving power and the error rate under the standard atmospheric pressure environment and the highland and mountain atmospheric pressure environment are compared, and the standard atmospheric condition parameters are set as follows: the temperature is 22 ℃, the air pressure is 1013mbar and the humidity is 50%; the mountain condition parameters of the plateau are set as follows: the temperature is 15 ℃, the air pressure is 807mbar, the humidity is 40%, and the simulation results are shown in fig. 4 and 5, and the receiving power is generally larger than that of the standard atmospheric pressure environment in the mountain area of the plateau, because the receiving power is higher than that of the standard atmospheric pressure environment as the altitude of the mountain area of the plateau increases, the atmospheric pressure and the humidity decrease, the oxygen and water molecule content in the atmosphere decrease and the molecular absorption loss decreases. Fig. 5, following the same analysis, shows that the bit error rate of the plateau mountain environment channel is generally less than that of the standard atmospheric environment. Fig. 6 shows channel capacities in two atmospheric environments ranging from 0-60Gbit/s.
In Step5, the unmanned aerial vehicle position change design scheme is: the user is as the transmitter, and unmanned aerial vehicle is as the receiver to 1 meter interval distance forms a 100 meters mobile line, and unmanned aerial vehicle flight speed is 1m/s, changes the height of route again, observes the position of communication performance best unmanned aerial vehicle. The data result of channel path loss and bit error rate 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 meters and 52 meters, when the unmanned aerial vehicle arrives right above the user transmitter, the maximum gain of the antenna is along the horizontal direction of the X axis due to the half-wave dipole antenna carried by the base station of the unmanned aerial vehicle, the gain of the antenna at this time is minimum, a bump with increased loss appears in the data diagram, the unmanned aerial vehicle continues to move forward, and is further and further away from the user, and the path loss is increased slowly. And the path loss increases as the height of the drone increases. Fig. 8 shows a trend of bit error rate similar to the received power. It is worth noting that in the interval of 0-25 m and 75-100 m, the path loss and the error rate are larger due to the fact that the unmanned aerial vehicle is low in height, and the change of the antenna high-gain direction and the user antenna alignment angle is caused in the interval. And the result analysis is combined, so that the position with the best communication performance between the unmanned aerial vehicle and the user can be conveniently found.
In Step5, the design scheme for changing the modulation mode is as follows: the unmanned aerial vehicle is kept unchanged in height position, the unmanned aerial vehicle flies along a horizontal path at the height of 20 meters, the modulation modes are DPSK, PAM, QAM, PSK, FSK, MSK respectively, and as shown in fig. 9, 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 modeling processes of building a three-dimensional model of a real mountain scene, obtaining channel model parameters through simulation, analyzing statistical properties and performances of a communication channel, updating scene parameters to generate a new channel model and the like. In practice, the set frequency can reach the terahertz frequency band, the antenna selection variety is more, and the MIMO array antenna is also included. Obtaining some important channel model parameters through simulation analysis, and obtaining a relation curve of the error rate and the transmission distance of a receiving system in a plateau environment by using a method of error rate theoretical analysis under different modulation modes such as QPSK and the like, wherein the error rate gradually increases along with the increase of the transmission distance; under the mountain area of plateau, communication system is more reliable and stable.
The invention provides a method for generating the step channel parameters, which can be configured according to actual conditions, and can better simulate the characteristics of the terahertz communication channel of the actual mountain scene; the modeling method covers main parameter data of terahertz channel modeling, can change scene parameters to perform characteristic analysis of a dynamic updatable terahertz channel, and provides corresponding design suggestions for realizing reliable communication of terahertz of future mountain scenes.
While the present invention has been described in detail with reference to the drawings, the present invention is not limited to the above embodiments, and various changes can be made without departing from the spirit of the present invention within the knowledge of those skilled in the art.

Claims (1)

1. A method for modeling a mountain terahertz channel of an unmanned aerial vehicle based on ray tracing is characterized by comprising the following steps:
step1: establishing a real mountain scene three-dimensional model, and setting initial environment parameters, wherein the environment parameters comprise carrier frequency, receiving and transmitting distance, transmitting power, frequency bandwidth and antenna angle;
step2: according to the set environmental parameters, the rays trace all paths from the transmitting end to the receiving end, channel model parameters are given through simulation, and a signal intensity distribution map 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;
step3: obtaining channel statistical characteristics including delay spread, molecular absorption loss, complex impulse response and channel H matrix according to channel model parameters;
step4: analyzing channel statistical characteristics, developing and researching bit error rate and throughput, and evaluating the performance of a scene communication system;
step5: adjusting scene parameters, and returning to Step1 to generate a new channel model and analyze channel characteristics by changing modulation modes, atmospheric environment parameters and vertical and horizontal positions of the unmanned aerial vehicle;
the building of the three-dimensional model of the real mountain scene is specifically as follows: firstly, downloading digital elevation data of an actual mountain scene from a remote sensing data website, and then using corresponding GIS software to carry out post-processing works 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, a transmitter, a receiver and position distribution of the unmanned aerial vehicle;
in Step2, the received power refers to the sum of powers of the effective paths from the transmitting end to the receiving end, and in the free space with the antenna mode, the expression is as follows:
wherein P is T For time-averaged radiation power, θ D And phi D For the direction of the ray leaving the emitter, θ A And phi A R represents the distance between the transmitter and the receiver for 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)
in Step2, the path loss refers to the loss of energy and power during propagation from the transmitting end to the receiving end, and the gain of the transmitting antenna is G T The gain of the 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)
wherein G is T，Max G for maximum gain of transmitting antenna R，Max For maximum gain of the receiving antenna, L S Representing the sum of all other losses in the system, including the bandwidth overlap factor;
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 terahertz waves, and the molecular absorption loss L of the content of oxygen and water vapor in the atmosphere on terahertz wave bands air Expressed as:
wherein, 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 The effective height of the water vapor is that of the communication elevation angle theta;
in Step3, the complex impulse response means that the transmission signal is an impulse signal, and through multipath propagation, the channel impulse response corresponds to superposition of paths at the receiving antenna, and is expressed as:
wherein N is the number of multipaths, a n Representing multipath propagation attenuation factor, τ n For the multipath propagation delay,is the multipath propagation phase;
in Step4, the bit error rate is obtained by setting the power density and the signal bandwidth of the environmental noise, and the bit error rate and the throughput are further used for calculating:
SNR(dB)＝10log 10 (P R (i))-10log 10 (N total )
wherein P is R Is the power received from the transmitter, N total The bit error rate is calculated according to an additive white gaussian noise model, which is abbreviated as AWGN, and the expression of BER when the AWGN exists is as follows under the condition that the AWGN does not consider any dispersion effect of a channel:
wherein P is 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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