Interruption probability evaluation method for intelligent reflecting surface assisted unmanned aerial vehicle communication system

Abstract

The application provides an outage probability evaluation method based on an intelligent reflecting surface assisted unmanned aerial vehicle communication system. The method comprises the following steps: initializing model parameters of the IRS assisted UAV communication system, calculating the impulse response from the transmitter to the reflecting surface end and the impulse response from the reflecting surface to the receiver end, calculating the total impulse response of the IRS assisted UAV communication system according to the impulse response from the transmitter to the reflecting surface end and the impulse response from the reflecting surface to the receiver end, calculating the optimal phase of the intelligent reflecting surface according to the total impulse response of the IRS assisted UAV communication system, and calculating the outage probability of the IRS assisted UAV communication system according to the optimal phase of the intelligent reflecting surface. The application models the wave propagation environment of the IRS assisted UAV scene through the geometric modeling theory. The channel model considers the multipath effect, path loss, and shadow fading, and tries to achieve the purpose of simulating the wireless propagation environment, so that the performance analysis of the IRS assisted UAV system becomes real and reliable.

Description

Technical Field

[0001] The present invention relates to the field of wireless communication technology, and in particular to an interruption probability assessment method based on an intelligent reflective surface-assisted unmanned aerial vehicle communication system. Background Art

[0002] In recent years, intelligent reflecting surfaces (IRS) have seen rapid development. This is because IRSs can intelligently adjust the reflection phase to control the wireless propagation environment, thereby providing additional support for line-of-sight links. Based on these characteristics, IRSs are gradually being integrated into various wireless technologies. Furthermore, due to their low cost and three-dimensional (3D) mobility, unmanned aerial vehicles (UAVs) have been considered a hot topic in academia and industry. Clearly, the combination of IRSs and UAVs is expected to become one of the most promising research directions in sixth-generation wireless communications. To uncover their potential applications in engineering construction, performance analysis of IRS-assisted UAV systems is essential.

[0003] A solution in the prior art discloses a method for analyzing the confidentiality performance of an IRS-assisted UAV relay system in the presence of multiple ground eavesdroppers, revealing the impact of the number of IRS elements and the position of the UAV on the probability of confidentiality interruption.

[0004] Another prior art approach discloses a performance analysis method for an IRS-assisted UAV system in an IoT scenario. Closed-form expressions for symbol error rate, ergodic channel capacity, and outage probability are derived. The effects of the number of IRS elements and the UAV's location on these expressions are also revealed.

[0005] Another prior art approach discloses a performance analysis method for an IRS-assisted UAV system. Two different methods are proposed to represent the probability density function of the instantaneous signal-to-noise ratio. Closed-form expressions for the outage probability and average bit error rate are derived. The impact of the UAV's location on these expressions is analyzed.

[0006] The shortcomings of the aforementioned existing solutions are as follows: Although they analyze the performance of IRS-assisted UAV systems and explore the impact of UAV-related parameters on system performance, these publicly available solutions are based on overly simplified channel models—time-invariant channel models that do not account for the Doppler effect between transceivers. While this approach effectively reduces the complexity of channel modeling and facilitates the derivation of closed-form expressions for system performance, it inherently fails to provide accurate insights for performance analysis. Therefore, existing solutions have not yet analyzed system performance based on realistic channel models. Summary of the Invention

[0007] The present invention provides an interruption probability assessment method for an intelligent reflective surface-assisted UAV communication system, providing guidance for the accurate design, development, and actual deployment of the system.

[0008] In order to achieve the above-mentioned purpose, the present invention adopts the following technical solutions.

[0009] A method for evaluating the interruption probability of a UAV communication system assisted by an intelligent reflective surface comprises:

[0010] Initialize the model parameters of the IRS-assisted UAV communication system;

[0011] Calculate the impulse response from the transmitter to the reflector and the impulse response from the reflector to the receiver;

[0012] The total impulse response of the IRS-assisted UAV communication system is calculated based on the impulse response from the transmitter to the reflector and the impulse response from the reflector to the receiver.

[0013] Calculating the optimal phase of the smart reflective surface based on the total impulse response of the IRS-assisted UAV communication system;

[0014] The interruption probability of the IRS-assisted UAV communication system is calculated according to the optimal phase of the smart reflecting surface.

[0015] Preferably, the initialization of the model parameters of the IRS-assisted UAV communication system includes:

[0016] Initialize the following model parameters of the IRS-assisted UAV communication system:

[0017] Initialize the number of antennas of the transmitter Tx to L T , the interval between adjacent antennas is d T ;

[0018] Initialize the number of antennas of the receiver Rx to L R , the interval between adjacent antennas is d R ;

[0019] Initialize the horizontal angle of the transmitting antenna relative to the x-axis and the elevation angle ψ relative to the xz plane T ;

[0020] Initialize the horizontal angle of the receiving antenna relative to the x-axis and the elevation angle ψ relative to the xz plane R ;

[0021] Initialize the movement speed of Rx R The horizontal angle γ relative to the x-axis R ;

[0022] Initialize the UAV's motion speed υ A , the horizontal angle γ relative to the x-axis A ;

[0023] Initialize the number of elements of IRS to N and the interval between adjacent elements to d A ;

[0024] Initialize the coordinates of the first element of IRS in the xoy plane to (x1, y1);

[0025] Initialize the number of scatterers to M;

[0026] Initialize the distance between Tx and Rx to D;

[0027] Initialize the heights of Tx, UAV, and Rx to be H T 、H A 、H R ;

[0028] The transmitted signal is sent from Tx to IRS, reflected by IRS, and then scattered by scatterers around Rx to Rx.

[0029] Preferably, the calculation of the impulse response from the transmitter to the reflecting surface includes:

[0030] The impulse response from the transmitter to the reflecting surface is Expressed as:

[0031]

[0032] Where k0 = 2π / λ is the free space wave number, λ = c0 / f c is the wavelength, c0 is the speed of light, f c is the carrier frequency, ε pn is the propagation distance from the pth transmitting antenna to the nth IRS element, expressed as:

[0033]

[0034] Among them, θ Tn It represents the elevation angle of Tx relative to UAV, expressed as:

[0035]

[0036] Among them, x n with y n They represent the coordinates of the nth IRS element in the xoy plane, as follows:

[0037]

[0038] in, Indicates rounding down, Δ T Indicates the distance from the pth transmitting antenna to the center of the transmitting antenna, p = 1, 2, ..., L T , expressed as:

[0039]

[0040] Doppler shift f TA It is expressed as follows:

[0041]

[0042] in, represents the horizontal angle of arrival for a line-of-sight path and is expressed as follows:

[0043]

[0044] PL TA Indicates the path loss from Tx to IRS, as shown below:

[0045]

[0046] in, represents the path loss factor, X σ Represents shadow fading, with a mean of 0 and a variance of The complex Gaussian distribution of .

[0047] Preferably, the calculation of the impulse response from the reflecting surface to the receiver includes:

[0048] The impulse response matrix from the reflector to the receiver is To describe, It is composed of the line-of-sight component and the non-line-of-sight component, expressed as:

[0049]

[0050] in, They represent the line-of-sight link and non-line-of-sight link from the reflecting surface to the receiver, respectively, and are further expressed as:

[0051]

[0052] Among them, K AR is the Rice factor, φ m is a random variable uniformly distributed on [-π,π), ε nq is the propagation distance from the nth IRS element to the qth receiving antenna, expressed as:

[0053]

[0054] in, It represents the horizontal acceptance angle of the line-of-sight path and is expressed as follows:

[0055]

[0056] θ Rn Indicates the elevation angle of AIRS relative to Rx, expressed as follows:

[0057]

[0058] Among them, Δ R Indicates the qth (q=1,2,…,L R ) The distance from the receiving antenna to the center of the receiving antenna is expressed as:

[0059]

[0060] ε nm is the propagation distance from the nth IRS element to the mth scatterer, expressed as:

[0061]

[0062] ε mq is the propagation distance from the mth scatterer to the qth receiving antenna, expressed as:

[0063]

[0064] in, represents the radius of the cylinder's base, is the horizontal arrival angle of the electromagnetic wave acting on the mth scatterer, is the vertical arrival angle acting on the mth scatterer, further expressed as:

[0065] Doppler shift f AR,LoS and f AR,NLoS They are represented as follows:

[0066]

[0067]

[0068] in, PL AR Indicates the path loss from IRS to Rx, as shown below:

[0069]

[0070] When the number of scatterers is infinite, that is, M→∞, the discrete random variable and Use continuous random variables αR 、R S 、H S Instead, use the von Mises distribution to describe α R , expressed as:

[0071]

[0072] Among them, α μ ∈[-π,π] represents the horizontal horizontal arrival angle, k represents the concentration of scatterers around Rx, I0(·) represents the first-order zero-order modified Bessel function, and hyperbolic distribution is used to describe R S , expressed as:

[0073]

[0074] Among them, u S ∈(0,1) represents the extent of the scatterer around Rx, R S,max Represents the maximum value of the base radius of the cylinder, and uses lognormal distribution to describe H S , expressed as

[0075]

[0076] Among them, H S,mean and σ S H S The mean and standard deviation of H S,max Indicates the maximum value of the cylinder height. Considering the randomness of the scatterer position, the set and Contains random terms, expressed as:

[0077]

[0078]

[0079] Among them, i represents a random variable that is uniformly distributed on [-1 / 2,1 / 2].

[0080] Preferably, the calculating of the total impulse response of the IRS-assisted UAV communication system based on the impulse response from the transmitter to the reflecting surface end and the impulse response from the reflecting surface to the receiver end includes:

[0081] The total impulse response of the IRS-assisted UAV system Expressed as:

[0082]

[0083] in, represents the impulse response from the transmitter to the reflecting surface at time t,

[0084] is the impulse response from the reflecting surface to the receiver at time t,

[0085] is the reflection matrix of IRS at time t, τ n ∈(0,1] and Represent the amplitude and phase of the nth IRS element respectively.

[0086] Preferably, the step of calculating the optimal phase of the smart reflective surface based on the total impulse response of the IRS-assisted UAV communication system includes:

[0087] The optimization problem of the optimal phase of the smart reflector is expressed as:

[0088]

[0089] Based on complex number operation rules and a series of calculations, the above formula can be further expressed as:

[0090]

[0091] in,

[0092] φ(t)=atan²(Q(t),I(t)), where atan²(y,x) represents the inverse tangent of y / x;

[0093] Based on the above formula, the optimization problem of the optimal phase of the smart reflector is further expressed as follows:

[0094]

[0095] According to the above formula, the optimal phase of IRS is obtained It is expressed as follows:

[0096]

[0097] Here, mod(·) represents the modulo operator.

[0098] Preferably, the calculation of the interruption probability of the IRS-assisted UAV communication system according to the optimal phase of the smart reflective surface includes:

[0099] The outage probability of the IRS-assisted UAV communication system refers to the end-to-end instantaneous channel capacity C(t) being lower than a predefined threshold C th The probability of , that is:

[0100] P out (t)=Pr(C(t)<Cth )

[0101] in, Represents the average transmit signal-to-noise ratio.

[0102] As can be seen from the technical solutions provided by the aforementioned embodiments of the present invention, the present invention uses geometric modeling theory to model the radio wave propagation environment of IRS-assisted UAV scenarios. This channel model takes into account multipath effects, path loss, and shadow fading, maximizing the simulation of the wireless propagation environment. This makes the performance analysis of the IRS-assisted UAV system realistic and reliable.

[0103] Additional aspects and advantages of the present invention will be set forth in part in the following description, will become apparent from the following description, or may be learned by practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0104] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0105] Figure 1 This is a flowchart of a method for evaluating the interruption probability of an IRS-assisted UAV communication system provided by an embodiment of the present invention.

[0106] Figure 2 2 is a schematic diagram of an IRS-assisted UAV communication system model according to an embodiment of the present invention.

[0107] Figure 3 It is a schematic diagram of a channel model corresponding to the system model described in an embodiment of the present invention.

[0108] Figure 4 This is an effect diagram of the interruption probability and the transmission power at different carrier frequencies according to an embodiment of the present invention.

[0109] Figure 5 This is a diagram showing the effect of interruption probability and transmission power when the number of IRS elements and Ricean factors are different in an embodiment of the present invention. DETAILED DESCRIPTION

[0110] The embodiments of the present invention are described in detail below, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and are not to be construed as limiting the present invention.

[0111] It will be understood by those skilled in the art that, unless expressly stated otherwise, the singular forms "a", "an", "said" and "the" used herein may also include the plural forms. It should be further understood that the term "comprising" used in the description of the present invention refers to the presence of the features, integers, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or groups thereof. It should be understood that when we refer to an element as being "connected" or "coupled" to another element, it may be directly connected or coupled to the other element, or there may be intermediate elements. In addition, "connected" or "coupled" as used herein may include wireless connections or couplings. The term "and / or" used herein includes any unit and all combinations of one or more associated listed items.

[0112] It will be understood by those skilled in the art that, unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by those skilled in the art in the art to which the present invention pertains. It should also be understood that terms such as those defined in common dictionaries should be understood to have meanings consistent with their meanings in the context of the prior art and, unless defined as such herein, will not be interpreted in an idealized or overly formal sense.

[0113] To facilitate understanding of the embodiments of the present invention, several specific embodiments will be further explained below with reference to the accompanying drawings, and each embodiment does not constitute a limitation on the embodiments of the present invention.

[0114] To accommodate the radio wave propagation environment in IRS-assisted UAV scenarios, this paper proposes a channel model that comprehensively considers multipath effects, path loss, and shadow fading. Based on this channel model, the system outage probability is analyzed.

[0115] The processing flow of the interruption probability assessment method based on the intelligent reflective surface assisted UAV communication system provided by the embodiment of the present invention is as follows: Figure 1 The specific implementation steps are as follows:

[0116] Step S1: Initialize the model parameters of the IRS-assisted UAV communication system.

[0117] Figure 2 This is a schematic diagram of the IRS-assisted UAV communication system model according to an embodiment of the present invention. The initialization steps are as follows:

[0118] Initialize the number of antennas of the transmitter (Tx) to L T , the interval between adjacent antennas is d T ;

[0119] Initialize the number of antennas of the receiver (Receiver, Rx) to L R , the interval between adjacent antennas is d R ;

[0120] Initialize the horizontal angle (relative to the x-axis) and elevation angle (relative to the xz plane) of the transmitting antenna to be and ψ T ;

[0121] Initialize the horizontal angle (relative to the x-axis) and elevation angle (relative to the xz plane) of the receiving antenna to be and ψ R ;

[0122] Initialize the movement speed and horizontal angle (relative to the x-axis) of Rx as υ R and γ R ;

[0123] Initialize the UAV's velocity and horizontal angle (relative to the x-axis) as υ A and γ A ;

[0124] Initialize the number of elements of IRS to N and the interval between adjacent elements to d A ;

[0125] Initialize the coordinates of the first element of IRS in the xoy plane to (x1, y1);

[0126] Initialize the number of scatterers to M;

[0127] Initialize the distance between Tx and Rx to D;

[0128] Initialize the heights of Tx, UAV, and Rx to be H T 、H A 、H R ;

[0129] Assuming that the Tx signal cannot directly reach the Rx due to obstruction by ground scatterers, the transmitted signal can only be sent from the Tx to the IRS, reflected by the IRS, and then scattered by scatterers around the Rx before reaching the Rx.

[0130] Step S2: Calculate the impulse response from the transmitter to the reflecting surface end.

[0131] Figure 3 Schematic diagram of the geometric channel model corresponding to the system model described in the embodiment of the present invention. The impulse response from the transmitter to the reflector end is It can be expressed as:

[0132]

[0133] Where k0 = 2π / λ is the free space wave number, λ = c0 / f c is the wavelength, c0 is the speed of light, f c is the carrier frequency, ε pn is the propagation distance from the pth transmitting antenna to the nth IRS element, which can be expressed as:

[0134]

[0135] Among them, θ Tn It represents the elevation angle of Tx relative to UAV and can be expressed as:

[0136]

[0137] Among them, x n with y n They represent the coordinates of the nth IRS element in the xoy plane, which can be expressed as follows:

[0138]

[0139] in, Indicates rounding down. T Indicates the pth (p=1,2,…,L T ) The distance from the transmitting antenna to the center of the transmitting antenna can be expressed as:

[0140]

[0141] Doppler shift f TA It can be expressed as follows:

[0142]

[0143] in, represents the horizontal angle of arrival for a line-of-sight path and is expressed as follows:

[0144]

[0145] In addition, PL TA The path loss from Tx to IRS can be expressed as follows:

[0146]

[0147] in, represents the path loss factor, X σ Represents shadow fading, with a mean of 0 and a variance of The complex Gaussian distribution of .

[0148] Step S3: Calculate the impulse response from the reflection surface to the receiver end.

[0149] The impulse response from the reflecting surface to the receiver can be expressed using the matrix To describe, by Figure 2 It can be seen that It is composed of the line-of-sight component and the non-line-of-sight component, which can be expressed as

[0150]

[0151] in, They represent the line-of-sight link and non-line-of-sight link from the reflecting surface to the receiver, respectively, and are further expressed as:

[0152]

[0153] Among them, K AR is the Rice factor, φ m is a random variable uniformly distributed on [-π,π), ε nq is the propagation distance from the nth IRS element to the qth receiving antenna, which can be expressed as:

[0154]

[0155] in, It represents the horizontal acceptance angle of the line-of-sight path and is expressed as follows:

[0156]

[0157] θ Rn Indicates the elevation angle of AIRS relative to Rx, expressed as follows:

[0158]

[0159] Among them, Δ R Indicates the qth (q=1,2,…,L R ) The distance from the receiving antenna to the center of the receiving antenna can be expressed as

[0160]

[0161] In addition, ε nm is the propagation distance from the nth IRS element to the mth scatterer, which can be expressed as

[0162]

[0163] ε mq is the propagation distance from the mth scatterer to the qth receiving antenna, which can be expressed as

[0164]

[0165] in, represents the radius of the cylinder's base, is the horizontal arrival angle of the electromagnetic wave acting on the mth scatterer, is the vertical arrival angle acting on the mth scatterer, which can be further expressed as

[0166] In addition, the Doppler shift f AR,LoS and f AR,NLoS They are represented as follows:

[0167]

[0168] in, PL AR The path loss from IRS to Rx can be expressed as follows:

[0169]

[0170] When the number of scatterers is infinite, that is, M→∞, the discrete random variable and The continuous random variable α can be used R 、R S 、H S Instead. In this patent, von Mises distribution is used to describe α R , which can be expressed as

[0171]

[0172] Among them, α μ ∈[-π,π] represents the average horizontal arrival angle, k represents the concentration of scatterers around Rx, and I0(·) represents the first-order modified Bessel function. Hyperbolic distribution is used to describe R S , which can be expressed as

[0173]

[0174] Among them, u S ∈(0,1) represents the extent of the scatterer around Rx, R S,max represents the maximum radius of the cylinder base. Finally, the lognormal distribution is used to describe H S , which can be expressed as

[0175]

[0176] Among them, H S,mean and σ S H S The mean and standard deviation of H S,max represents the maximum value of the cylinder height. It is obvious that the proposed model relies on discrete parameters, namely and Considering the randomness of the scatterer positions, the set and Should contain random terms, which can be expressed as

[0177]

[0178]

[0179] Among them, i represents a random variable that is uniformly distributed on [-1 / 2,1 / 2].

[0180] Step S4: Calculate the total impulse response of the IRS-assisted UAV communication system.

[0181] Total impulse response of the proposed IRS-assisted UAV system It can be expressed as

[0182]

[0183] in, represents the impulse response from the transmitter to the reflecting surface at time t, is the impulse response from the reflecting surface to the receiver at time t,

[0184] is the reflection matrix of IRS at time t, τ n ∈(0,1] and Represent the amplitude and phase of the nth IRS element respectively.

[0185] Step S5: Calculate the optimal phase of the smart reflective surface.

[0186] In order to maximize the received signal amplitude, the corresponding optimization problem can be expressed as:

[0187]

[0188] Based on complex number operation rules and a series of calculations, the above formula can be further expressed as:

[0189]

[0190] in,

[0191] φ(t)=atan2(Q(t),I(t)), where atan2(y,x) represents the inverse tangent of y / x.

[0192] Based on the above formula, the optimization problem can be further expressed as follows:

[0193]

[0194] According to the above formula, the optimal phase of IRS is obtained As shown below:

[0195]

[0196] Here, mod(·) represents the modulo operator.

[0197] According to the optimal phase of IRS The amplitude of the total impulse response H(t) of the IRS-assisted UAV system can be maximized, thereby maximizing the channel capacity and reducing the system outage probability.

[0198] Step S6: Calculate the interruption probability of the IRS-assisted UAV communication system.

[0199] The outage probability of the proposed IRS-assisted UAV communication system refers to the probability that the end-to-end instantaneous channel capacity C(t) is lower than a predefined threshold C th The probability of , that is:

[0200] P out (t)=Pr(C(t)<C th )

[0201] in, Represents the average transmit signal-to-noise ratio.

[0202] The total impulse response H(t) above includes the optimal phase of the IRS

[0203] The interruption probability calculated above can be used to measure the frequency of communication system interruptions. This present invention uses this metric to evaluate the communication quality of an IRS-assisted UAV communication system. A lower interruption probability indicates better communication quality; a higher interruption probability indicates worse communication quality.

[0204] The following specifically illustrates a method for evaluating the interruption probability of a UAV communication system based on an intelligent reflective surface through the accompanying drawings and examples. In this example, the specific simulation parameters are shown in Table 1.

[0205] Table 1 Simulation parameters

[0206]

[0207]

[0208] Figure 4 The figure shows the effect of outage probability and transmission power at different carrier frequencies. Figure 4It can be seen that the outage probability increases with the increase of the carrier frequency. This is because a larger carrier frequency results in a larger path loss. More specifically, for a given P out (t) = 10 -3 When f c The transmit power decreases by 24 dBm from 30 GHz to 2.4 GHz. It is further observed that the outage probability increases with the increase of the UAV speed in the sub-6 GHz band, but the trend is just the opposite in the mmWave band. This means that the UAV is more suitable in the mmWave band when in a high mobility scenario.

[0209] The increase of the UAV speed. But in the mmWave band, the trend is just the opposite. This means that the UAV is more suitable in the mmWave band when in a high mobility scenario.

[0210] Figure 5 The outage probability and the effect of the transmit power are shown when the number of IRS elements and the Rician factor are different. From Figure 5 It can be seen that the outage probability increases with the increase of the carrier frequency. This is because a larger carrier frequency results in a larger path loss. More specifically, for a given P out (t) = 10 -3 and K AR = 0 dB, the transmit power decreases by 5 dBm as N increases from 9 to 16. In addition, it can also be observed that the outage probability decreases with the increase of the number of elements. This is because the larger the value of N, the stronger the received signal strength, resulting in better transmission performance. Finally, it can also be observed that the outage probability decreases significantly with the increase of the Rician factor.

[0211] In summary, the outage probability evaluation method of the IRS-assisted UAV communication system proposed in the embodiments of the present application provides a way for evaluating the performance analysis of the existing IRS-assisted UAV system. The embodiments of the present application provide an outage probability evaluation method for an IRS-assisted UAV system. The geometric random channel modeling method is used to represent the radio propagation environment of the IRS-assisted UAV communication scenario, thereby effectively improving the accuracy of performance analysis.

[0212] Those skilled in the art can understand that the modules or flows in the drawings are not necessarily required to implement the present application.

[0213] From the above description of the embodiments, those skilled in the art can clearly understand that the present application can be implemented by means of software and the necessary general hardware platform. Based on such understanding, the technical solutions of the present application can be embodied in the form of a software product, which can be stored in a storage medium, such as a ROM / RAM, a magnetic disk, an optical disk, etc., and includes a number of instructions to make a computer device (which can be a personal computer, a server, or a network device, etc.) execute the methods described in various embodiments or some parts of the embodiments.

[0214] Each embodiment in this specification is described in a progressive manner. The same or similar parts between the embodiments can be referred to each other. Each embodiment focuses on the differences from other embodiments. In particular, for the device or system embodiments, since they are basically similar to the method embodiments, the description is relatively simple. For the relevant parts, refer to the partial description of the method embodiments. The device and system embodiments described above are merely schematic, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the scheme of this embodiment. A person of ordinary skill in the art can understand and implement it without making any creative efforts.

[0215] The above description is merely a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in the present invention should be included in the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be based on the scope of protection of the claims.

Claims

1. A method for evaluating the interruption probability of an intelligent reflective surface-assisted UAV communication system, characterized in that: include: Initialize the model parameters of the intelligent reflector IRS assisted UAV communication system; Calculate the impulse response from the transmitter to the reflector and the impulse response from the reflector to the receiver; The total impulse response of the IRS-assisted UAV communication system is calculated based on the impulse response from the transmitter to the reflector and the impulse response from the reflector to the receiver. Calculating the optimal phase of the smart reflective surface based on the total impulse response of the IRS-assisted UAV communication system; The interruption probability of the IRS-assisted UAV communication system is calculated based on the optimal phase of the smart reflective surface. The transmission signal is sent from Tx to IRS, reflected by IRS, and then scattered by scatterers around Rx to Rx. The IRS is located on the UAV; Optimal phase of IRS It is expressed as follows: Wherein, mod(·) represents the modulo operator; φ(t)=atan2(Q(t),I(t)), atan2(y,x) represents the inverse tangent of y / x, φ m is a random variable uniformly distributed on [-π,π), k0=2π / λ is the free space wave number, ε nm is the propagation distance from the nth IRS element to the mth scatterer, f TA is the Doppler shift in the impulse response from the transmitter to the reflector, f AR,NLoS represents the Doppler shift of the non-line-of-sight component in the impulse response from the reflecting surface to the receiver, ε pn is the propagation distance from the pth transmitting antenna to the nth IRS element, ε mq represents the propagation distance from the mth scatterer to the qth receiving antenna.

2. The method according to claim 1, characterized in that The model parameters of the initialization IRS-assisted UAV communication system include: Initialize the following model parameters of the IRS-assisted UAV communication system: Initialize the number of antennas of the transmitter Tx to L T , the interval between adjacent antennas is d T ; Initialize the number of antennas of the receiver Rx to L R , the interval between adjacent antennas is d R ; Initialize the horizontal angle of the transmitting antenna relative to the x-axis and the elevation angle ψ relative to the xz plane T ; Initialize the horizontal angle of the receiving antenna relative to the x-axis and the elevation angle ψ relative to the xz plane R ; Initialize the movement speed of Rx R The horizontal angle γ relative to the x-axis R ; Initialize the UAV's motion speed υ A , the horizontal angle γ relative to the x-axis A ; Initialize the number of elements of IRS to N and the interval between adjacent elements to d A ; Initialize the coordinates of the first element of IRS in the xoy plane to (x1, y1); Initialize the number of scatterers to M; Initialize the distance between Tx and Rx to D; Initialize the heights of Tx, UAV, and Rx to be H T 、H A 、H R .

3. The method according to claim 2, characterized in that The calculation of the impulse response from the transmitter to the reflecting surface includes: The impulse response from the transmitter to the reflecting surface is Expressed as: Where k0 = 2π / λ is the free space wave number, λ = c0 / f c is the wavelength, c0 is the speed of light, f c is the carrier frequency, ε pn is the propagation distance from the pth transmitting antenna to the nth IRS element, expressed as: Among them, θ Tn It represents the elevation angle of Tx relative to the UAV, expressed as: Among them, x n with y n They represent the coordinates of the nth IRS element in the xoy plane, as follows: in, Indicates rounding down, Δ T Indicates the distance from the pth transmitting antenna to the center of the transmitting antenna, p = 1, 2, ..., L T , expressed as: Doppler shift f TA It is expressed as follows: in, represents the horizontal angle of arrival for a line-of-sight path and is expressed as follows: PL TA Indicates the path loss from Tx to IRS, as shown below: in, represents the path loss factor, X σ Represents shadow fading, with a mean of 0 and a variance of The complex Gaussian distribution of .

4. The method according to claim 3, characterized in that The calculation of the impulse response from the reflecting surface to the receiver includes: The impulse response matrix from the reflector to the receiver is To describe, It is composed of the line-of-sight component and the non-line-of-sight component, expressed as: in, They represent the line-of-sight link and non-line-of-sight link from the reflecting surface to the receiver, respectively, and are further expressed as: Among them, K AR is the Rice factor, φ m is a random variable uniformly distributed on [-π,π), ε nq is the propagation distance from the nth IRS element to the qth receiving antenna, expressed as: in, It represents the horizontal acceptance angle of the line-of-sight path and is expressed as follows: θ Rn It represents the elevation angle of IRS relative to Rx and is expressed as follows: Among them, Δ R Indicates the distance from the qth receiving antenna to the center of the receiving antenna, q = 1, 2, ..., L R , expressed as: ε nm is the propagation distance from the nth IRS element to the mth scatterer, expressed as: ε mq is the propagation distance from the mth scatterer to the qth receiving antenna in, represents the radius of the cylinder's base, is the horizontal arrival angle of the electromagnetic wave acting on the mth scatterer, is the vertical arrival angle acting on the mth scatterer, further expressed as: Doppler shift f AR,LoS and f AR,NLoS They are represented as follows: in, PL AR Indicates the path loss from IRS to Rx, as shown below: When the number of scatterers is infinite, that is, M→∞, the discrete random variable and Use continuous random variables α R 、R S 、H S Instead, use the von Mises distribution to describe α R , expressed as: Among them, α μ ∈[-π,π] represents the horizontal horizontal arrival angle, k represents the concentration of scatterers around Rx, I0(·) represents the first-order zero-order modified Bessel function, and hyperbolic distribution is used to describe R S , expressed as: Among them, u S ∈(0,1) represents the extent of the scatterer around Rx, R S,max Represents the maximum value of the base radius of the cylinder, and uses lognormal distribution to describe H S , expressed as: Among them, H S,mean and σ S H S The mean and standard deviation of H S,max Indicates the maximum value of the cylinder height. Considering the randomness of the scatterer position, the set and Contains random terms, expressed as: Among them, i represents a random variable that is uniformly distributed on [-1 / 2,1 / 2].

5. The method according to claim 3, characterized in that The calculation of the total impulse response of the IRS-assisted UAV communication system based on the impulse response from the transmitter to the reflecting surface end and the impulse response from the reflecting surface to the receiver end includes: Total impulse response of the IRS-assisted UAV communication system Expressed as: in, represents the impulse response from the transmitter to the reflecting surface at time t, is the impulse response from the reflecting surface to the receiver at time t, is the reflection matrix of IRS at time t, τ n ∈(0,1] and Represent the amplitude and phase of the nth IRS element respectively.

6. The method according to claim 5, characterized in that The step of calculating the optimal phase of the smart reflective surface based on the total impulse response of the IRS-assisted UAV communication system includes: The optimization problem of the optimal phase of the smart reflector is expressed as: Based on the complex number operation rules, the above formula can be further expressed as: in, ε nq is the propagation distance from the nth IRS element to the qth receiving antenna; The optimization problem of the optimal phase of the smart reflector is further expressed as follows:

7. The method according to claim 6, characterized in that The method of calculating the interruption probability of the IRS-assisted UAV communication system according to the optimal phase of the intelligent reflecting surface includes: The outage probability of the IRS-assisted UAV communication system refers to the end-to-end instantaneous channel capacity C(t) being lower than a predefined threshold C th The probability of , that is: P out (t)=Pr(C(t)<C th , in, Represents the average transmit signal-to-noise ratio.

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