Airborne IRS-assisted vehicle-to-vehicle communication channel simulation method and system

Abstract

The present invention relates to an aerial IRS-assisted vehicle-to-vehicle communication channel simulation method and system, including: S1 constructing an IRS-assisted vehicle-to-vehicle communication scenario, where the transmitting station and the receiving station are respectively equipped with linear arrays, an IRS is deployed on a drone, and the IRS rotates in three-dimensional space with the movement of the drone, and a channel matrix is constructed based on set scenario parameters; S2 decomposing the IRS communication channel into Tx-IRS subchannels, IRS-Rx subchannels, and Tx-Rx subchannels, where Tx is the transmitting end and Rx is the receiving end, and channel transfer functions of the three subchannels are constructed respectively; S3 constructing a channel transfer function of the IRS-assisted model based on the subchannel transfer functions obtained in S2; S4 optimizing the reflection phase of the IRS with the goal of maximizing the received power; and S5 obtaining the corresponding space-time-frequency correlation function based on the channel transfer function optimized in S4. The IRS is carried on the drone, and the wireless signal sent by the transmitting end is reflected by the IRS. By adjusting the phase of the reflection unit, a virtual beam aligned with the receiving end is formed, thereby improving the performance of the communication system.

Description

Technical Field

[0001] The present invention relates to the technical field of communication simulation, and in particular to an aerial IRS-assisted vehicle-to-vehicle communication channel simulation method and system. Background Art

[0002] The statements in this section merely provide background information related to the present invention and do not necessarily constitute prior art.

[0003] Intelligent Reflecting Surface (IRS) is a technology that integrates a large number of low-cost passive reflective elements on a plane to intelligently reconfigure the wireless propagation environment, thereby significantly improving the performance of wireless communication networks.

[0004] Research on IRS channel modeling is still in its infancy. Existing channel models are mostly based on line-of-sight, ignoring key factors such as the reflector radiation pattern and IRS rotation. Their relatively simple structures make these models inaccurate when evaluating real-world IRS communication systems. Furthermore, existing IRS models are often deployed on building surfaces or walls, failing to fully utilize three-dimensional space, resulting in suboptimal communication models. Summary of the Invention

[0005] In order to solve the technical problems existing in the above-mentioned background technology, the present invention provides an aerial IRS-assisted vehicle-to-vehicle communication channel simulation method and system. The IRS is carried on a drone. The wireless signal sent by the transmitter is reflected by the IRS. By adjusting the phase of the reflection unit, a virtual beam aligned with the receiver is formed, thereby effectively improving the performance of the communication system.

[0006] In order to achieve the above object, the present invention adopts the following technical solutions:

[0007] A first aspect of the present invention provides an airborne IRS-assisted vehicle-to-vehicle communication channel simulation method, comprising the following steps:

[0008] S1: Construct an IRS-assisted vehicle-to-vehicle communication scenario. The transmitting and receiving stations are equipped with linear arrays. The IRS is deployed on the drone and rotates in three-dimensional space with the movement of the drone. The channel matrix is constructed based on the set scenario parameters.

[0009] S2: The IRS communication channel is decomposed into the Tx-IRS subchannel, the IRS-Rx subchannel, and the Tx-Rx subchannel, where Tx represents the transmitter and Rx represents the receiver. The channel transfer functions of the three subchannels are constructed respectively.

[0010] S3: Based on the sub-channel transfer function obtained in S2, the channel transfer function of the IRS auxiliary model is constructed;

[0011] S4: Optimize the IRS reflection phase with the goal of maximizing the received power;

[0012] S5: Based on the channel transfer function optimized in S4, the corresponding space-time-frequency correlation function is obtained.

[0013] A second aspect of the present invention provides a system for implementing the above method, comprising:

[0014] The communication scenario unit is configured to: construct an IRS-assisted vehicle-to-vehicle communication scenario, with the transmitting and receiving stations each equipped with a linear array. The IRS is deployed on the drone and rotates in three-dimensional space with the movement of the drone, and a channel matrix is constructed based on the set scenario parameters;

[0015] The sub-channel unit is configured to: decompose the IRS communication channel into a Tx-IRS sub-channel, an IRS-Rx sub-channel, and a Tx-Rx sub-channel, where Tx represents a transmitting end and Rx represents a receiving end, and construct channel transfer functions of the three sub-channels respectively;

[0016] The channel transfer function unit is configured to: construct a channel transfer function of the IRS auxiliary model based on the sub-channel transfer function obtained in the sub-channel unit;

[0017] The channel transfer function optimization unit is configured to: optimize the reflection phase of the IRS with the goal of maximizing the received power;

[0018] The channel simulation unit is configured to obtain a corresponding space-time-frequency correlation function based on the optimized channel transmission function.

[0019] A third aspect of the present invention provides a computer-readable storage medium.

[0020] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of the above-mentioned method for simulating a vehicle-to-vehicle communication channel assisted by an airborne IRS.

[0021] A fourth aspect of the present invention provides a computer device.

[0022] A computer device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, the steps of the above-described method for simulating a vehicle-to-vehicle communication channel assisted by an airborne IRS are implemented.

[0023] Compared with the existing technology, one or more of the above technical solutions have the following beneficial effects:

[0024] 1. By introducing an IRS mounted on a drone into a traditional vehicle-to-vehicle communication scenario, an airborne IRS-assisted vehicle-to-vehicle communication scenario was constructed. This method can reflect the impact of path loss, the rotation angle of the IRS when following the drone's movement, the reflection unit pattern, the drone's flight altitude, and speed on the statistical characteristics of the wireless channel.

[0025] 2. By optimizing the phase of IRS, the IRS auxiliary channel exhibits statistical characteristics similar to the direct path, and greatly reduces the multipath fading and Doppler spread of the channel.

[0026] 3. It makes up for the shortcomings of current IRS channel modeling and can provide support for the design and performance evaluation of IRS communication systems. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] The accompanying drawings, which constitute a part of the present invention, are used to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute improper limitations on the present invention.

[0028] Figure 1 This is a schematic diagram of a process flow for simulating a vehicle-to-vehicle communication channel assisted by an airborne IRS according to one or more embodiments of the present invention;

[0029] Figure 2 This is a schematic diagram of an IRS-assisted vehicle-to-vehicle communication scenario provided by one or more embodiments of the present invention;

[0030] Figure 3 1 is a schematic diagram of parameter definitions of an IRS-assisted vehicle-to-vehicle communication channel model provided by one or more embodiments of the present invention;

[0031] Figure 4 This is a schematic diagram of channel amplitude comparison based on optimized reflection phase and random reflection phase provided by one or more embodiments of the present invention. DETAILED DESCRIPTION

[0032] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0033] It should be noted that the following detailed descriptions are exemplary and intended to provide further explanation of the present invention. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which the present invention belongs.

[0034] It should be noted that the terms used herein are only for describing specific embodiments and are not intended to limit the exemplary embodiments according to the present invention. As used herein, unless the context clearly indicates otherwise, the singular form is intended to include the plural form. In addition, it should be understood that when the terms "comprise" and / or "include" are used in this specification, they indicate the presence of features, steps, operations, devices, components and / or combinations thereof.

[0035] As described in the background, research on IRS channel modeling is still in its infancy. Existing channel models are mostly based on line-of-sight, ignoring key factors such as the reflector radiation pattern and IRS rotation. Their relatively simple structure makes these models inaccurate when evaluating real-world IRS communication systems. Furthermore, existing IRS models are often deployed on building surfaces or walls, failing to fully utilize three-dimensional space, resulting in suboptimal communication model performance.

[0036] Therefore, the following embodiments provide a method and system for simulating a vehicle-to-vehicle communication channel using an aerial IRS. The IRS is mounted on a drone, and the wireless signal sent by the transmitter is reflected by the IRS. By adjusting the phase of the reflector unit, a virtual beam aligned with the receiver is formed, thereby effectively improving the performance of the communication system.

[0037] In drone communications, wireless channels often have a strong line-of-sight component. Drones are also highly maneuverable and can fully utilize three-dimensional space. They can fly at varying altitudes and maneuver flexibly in any direction. The onboard antenna array can be tilted at any angle, enabling three-dimensional rotation. An IRS (Infrared Reflection System) consists of a large number of low-cost passive reflective units, enabling passive beamforming. Adjusting the amplitude and phase of the reflective units can effectively improve the performance of the communication system. Combining these two technologies, using drones equipped with an IRS to construct an aerial IRS communication system has become a potential transmission solution for wireless communications. Compared to ground-based IRS communication systems, aerial IRS communication systems offer greater deployment flexibility, enable 360-degree panoramic reflection, and provide wider signal coverage, effectively improving communication quality for edge users.

[0038] Example 1:

[0039] like Figure 1-Figure 4 As shown, the airborne IRS-assisted vehicle-to-vehicle communication channel simulation method includes the following steps:

[0040] S1: Construct an IRS-assisted vehicle-to-vehicle communication scenario. The transmitting and receiving stations are equipped with linear arrays. The IRS is deployed on the drone. It rotates in three-dimensional space with the movement of the drone and constructs a channel matrix based on the set scenario parameters.

[0041] S2: Based on the IRS communication channel in the channel matrix, it is decomposed into Tx-IRS sub-channel, IRS-Rx sub-channel and Tx-Rx sub-channel, where Tx represents the transmitter and Rx represents the receiver. The channel transfer functions of the three sub-channels are constructed respectively.

[0042] S3: Based on the sub-channel transfer function obtained in S2, the channel transfer function of the IRS auxiliary model is constructed;

[0043] S4: Optimize the IRS reflection phase with the goal of maximizing the received power;

[0044] S5: Based on the channel transfer function optimized in S4, the corresponding space-time-frequency correlation function is obtained.

[0045] Specifically:

[0046] like Figure 2 As shown in the figure, assuming the line-of-sight component of the transmitter and receiver is blocked by obstacles in the transmission scene, the wireless signal sent by the transmitter (Tx) is reflected by the IRS on the drone, forming a virtual beam aligned with the receiver (Rx). By adjusting the phase of the reflection unit, the communication system performance is effectively improved.

[0047] Figure 2 middle:

[0048] IRS: Intelligent Reflecting Surface, a technology that significantly improves the performance of wireless communication networks by integrating a large number of low-cost passive reflective elements on a plane to reconfigure the wireless propagation environment.

[0049] LoS and NLoS: (line-of-sight) and (non-line-of-sight), respectively, refer to line-of-sight and non-line-of-sight transmission of wireless signals. The propagation conditions of wireless communication systems are divided into line-of-sight and non-line-of-sight environments. Under line-of-sight conditions, wireless signals propagate in a "straight line" between the transmitter and receiver without obstruction; under non-line-of-sight conditions, wireless signals can only reach the receiver through reflection, scattering, and diffraction.

[0050] S1: If Figure 3 In the IRS-assisted vehicle-to-vehicle communication scenario shown in the figure, the transmitting station and the receiving station are each equipped with a uniform linear array. An IRS is deployed on the drone, which can rotate in three-dimensional space with the movement of the drone. The number of transmitting array antenna elements (P), the number of receiving array antenna elements (Q), the number of IRS reflectors (K), and the spacing between adjacent antenna elements in the transmitting array (δ T ), the spacing between adjacent antenna elements in the receiving array (δ R ), the spacing between adjacent rows and columns of the IRS reflection unit (δ x,δ y ), transmit antenna array azimuth and elevation Receive antenna array azimuth and elevation Transmitting antenna moving speed (v T ), moving direction (α T ), receiving antenna moving speed (v R ), moving direction (α R ), UAV moving speed (v I ), moving direction (α I ), the IRS is rotated around the x-axis, y-axis, and z-axis by angles (α, β, γ).

[0051] S2: Decompose the IRS communication channel into three sub-channels, namely, Tx-IRS sub-channel, IRS-Rx sub-channel and Tx-Rx sub-channel, where Tx represents the transmitter and Rx represents the receiver;

[0052] S2(a): Construct the channel transfer function of the Tx-IRS subchannel;

[0053] S2(b): Construct the channel transfer function of the IRS-Rx subchannel;

[0054] S2(c): Construct the transfer function of the Tx-Rx subchannel;

[0055] S3: Based on the sub-channel transfer function, construct the IRS-assisted channel transfer function;

[0056] S4: Optimize the IRS reflector phase based on the principle of maximum received power;

[0057] S5: Derivation of the corresponding space-time-frequency correlation function based on the channel transfer function of IRS-assisted communication;

[0058] In step S1, the channel matrix is as follows:

[0059] H=H TI ΘH IR +H TR

[0060] Among them, H TI 、H IR and H TR Represent the channel matrices of Tx-IRS, IRS-Rx, and Tx-Rx subchannels respectively. is the reflection coefficient matrix of IRS, where diag(·) is an operation that converts the contained elements into a diagonal matrix, Γ k and ψ k represent the amplitude and phase shift of the kth reflection unit respectively.

[0061] In step S2, at time t and frequency f, the channel transfer function from the pth transmitting antenna to the qth receiving antenna is expressed as follows:

[0062]

[0063] Among them, H TI,kp (t,f) represents the channel transfer function between the pth transmitting antenna and the kth reflecting unit, H IR,qk (t,f) represents the channel transfer function between the kth reflection unit and the qth receiving antenna, H TR,qp (t,f) represents the channel transfer function between the pth transmitting antenna and the qth receiving antenna without passing through the IRS.

[0064] In step S2(a), the channel transfer function of the Tx-IRS subchannel is expressed as follows:

[0065]

[0066] The line-of-sight component and non-line-of-sight component of the channel transfer function are expressed as follows:

[0067]

[0068]

[0069] Among them, R TI represents the Ricean factor of the Tx-IRS subchannel, f c represents the carrier frequency, and λ is the wavelength. The superscript (n,m) represents the mth ray in the nth cluster. N TI is the number of clusters in the Tx-IRS subchannel, M n is the number of rays in the nth cluster. is the initial phase of the (n,m)th ray uniformly distributed in the interval [0,2π). Symbol PL TI represents the path loss of the direct path, represents the path loss of the (n,m)th ray. Denotes the power of the (n,m)th ray. The directional patterns of the pth transmitting antenna and the kth IRS reflector are represented by G p and G e express.

[0070] The directional pattern of the IRS reflector unit is as follows:

[0071]

[0072] in, is the angle between the IRS normal and the arrival ray. The path loss adopts the following model:

[0073]

[0074] Where c is the speed of light, D0 is the reference distance, n PLE is the path loss index. In addition, d is the propagation distance, that is, the length of the direct path is The non-straight path is

[0075] is the departure angle unit vector, expressed as follows:

[0076]

[0077] in To leave the elevation angle, is the departure azimuth.

[0078] is the arrival angle unit vector, expressed as follows:

[0079]

[0080] in, To reach the elevation angle, is the arrival azimuth.

[0081] u p is the position vector of the p-th transmitting antenna, which can be expressed as:

[0082]

[0083] u k is the position vector of the k-th IRS reflection unit, expressed as follows:

[0084]

[0085] in, is the initial position of the kth IRS reflection unit, which is defined as follows:

[0086]

[0087] Among them, K x and K y Indicates the number of rows and columns of reflection units in IRS Indicates rounding up, k y =k-(k x -1)K y , δ x and δ y Represents the row and column spacing of the reflection unit, H I Indicates the flight altitude of the drone.

[0088] The IRS rotates with the drone in the air, and the rotation matrix M R It is expressed as follows:

[0089]

[0090] Among them, α, β, and γ are the rotation angles of IRS around the x, y, and z axes, respectively.

[0091] The Doppler frequency due to Tx and IRS movement is expressed as follows:

[0092]

[0093] Among them, v T =v T ·[cosα T ,sinα T ,0] is the velocity vector of the transmitting antenna, v I =v I ·[cosα I ,sinα I ,0] is the velocity vector of the UAV.

[0094] In step S2(b), the channel transfer function of the IRS-Rx subchannel is expressed as follows:

[0095]

[0096] The channel transfer functions of the direct path component and the non-direct path component of the IRS-Rx subchannel are expressed as follows:

[0097]

[0098]

[0099] Among them, R IR is the Ricean factor of the IRS-Rx subchannel, N IR is the number of clusters in the IRS-Rx subchannel. is the initial phase of the (n,m)th ray uniformly distributed in the interval [0,2π). Symbol PL IR represents the path loss of the direct path, represents the path loss of the (n,m)th ray. Denotes the power of the (n,m)th ray. The directional pattern of the qth receiving antenna is represented by G q express, represents the angle between the (n,m)th ray reflected by the IRS and the IRS normal. is the departure angle unit vector, where To leave the pitch angle, To leave the horizontal angle. is the arrival angle unit vector, where To achieve the pitch angle, is the reaching horizontal angle. and They represent the line-of-sight component and the Doppler frequency caused by the movement of Rx and IRS in the non-direct path, and They represent the line-of-sight component and the time delay of the (n,m)th ray respectively.

[0100] is the Doppler frequency due to the movement of IRS and Rx, expressed as follows:

[0101]

[0102] Among them, v R =v R ·[cosα R ,sinα R ,0] is the velocity vector of Rx.

[0103] u q is the position coordinate of the qth receiving antenna, expressed as follows:

[0104]

[0105] In S2(c), assuming that the line-of-sight component of the Tx-Rx subchannel is blocked by an obstacle, the channel transfer function of the Tx-Rx subchannel can be expressed as:

[0106]

[0107] Among them, N TR is the number of clusters in the Tx-Rx subchannel, symbol is the initial phase of the (n,m)th ray uniformly distributed in the interval [0,2π). represents the path loss of the (n,m)th ray, Represents the power of the (n,m)th ray. is the departure angle unit vector, where To leave the pitch angle, To leave the horizontal angle. is the arrival angle unit vector, where To achieve the pitch angle, is the reaching horizontal angle. is the Doppler frequency caused by the motion of the transmitting and receiving antennas and can be expressed as:

[0108]

[0109] In step S3, the channel transfer function of the proposed IRS auxiliary channel model is as follows:

[0110]

[0111] Among them, H TI,kp (t,f),H IR,kp (t,f) and H TR,kp (t, f) are the channel transfer functions of the Tx-IRS, IRS-Rx and Tx-Rx sub-channels obtained in steps S2(a), S2(b) and S2(c), respectively.

[0112] In step S4, to maximize the received signal power, the multipath phases reflected by each reflector need to be aligned. Assuming that the IRS can obtain the positions of the Tx, Rx, and IRS in real time, the optimized phases satisfy the following conditions:

[0113]

[0114] Where C is a constant. It is worth noting that the direct path of the Tx-Rx subchannel is blocked by obstacles. Without loss of generality, set C = 0. In addition, the optimized reflection phase varies with time and frequency. k (t,f) is the reflection phase of the kth reflection unit, which can be expressed as:

[0115]

[0116] in, is the arrival angle unit vector in the Tx-IRS subchannel, is the departure angle unit vector in the IRS-Rx subchannel. and are the Doppler frequencies of the line-of-sight components in the Tx-IRS and IRS-Rx subchannels, and are the delays of the line-of-sight components in the Tx-IRS and IRS-Rx subchannels, respectively, and f c is the system carrier frequency, λ is the wavelength, u k is the local coordinate of the kth reflection unit.

[0117] In step S5, the space-time-frequency correlation function is used to characterize the correlation of channels between different antenna elements, different times, and different frequencies. The space-time-frequency correlation function of the proposed channel model is expressed as follows:

[0118]

[0119] Where Δt is the time interval, Δf is the frequency interval, (·) *is the complex conjugate operation, and E(·) is the expectation operation.

[0120] The space-time-frequency correlation function can be further written as:

[0121]

[0122] From the above formula, we can see that the space-time-frequency correlation function of the proposed channel model depends on the space-time-frequency correlation function of the Tx-IRS subchannel, that is, The space-time-frequency correlation function of the IRS-Rx subchannel is The space-time-frequency correlation function of the Tx-Rx subchannel is and the reflection coefficient of the IRS.

[0123] In the above formula, let Δf = 0 can obtain the time correlation function of the proposed IRS auxiliary channel.

[0124] If Δt=0 and Δf=0, the spatial correlation function of the proposed IRS auxiliary channel can be obtained.

[0125] Similarly, let Δt = 0, and The frequency correlation function of the proposed IRS auxiliary channel can be obtained.

[0126] For the convenience of expression, the line-of-sight component can be regarded as a special cluster containing only one ray. In addition, the path gains of the three proposed sub-channels are represented by the symbols x∈{TI,IR,TR} represents. For example, the path gain in the Tx-IRS subchannel is expressed as follows:

[0127]

[0128] Where superscript n=1,...,N TI represents the index of the non-line-of-sight component cluster, and n=0 represents the index of the line-of-sight component cluster.

[0129] The space-time-frequency correlation function of the Tx-IRS subchannel is expressed as follows:

[0130]

[0131] The above formula can be further expressed as:

[0132]

[0133] The space-time-frequency correlation function of the IRS-Rx subchannel can be expressed as:

[0134]

[0135] The above formula can be further expressed as:

[0136]

[0137] Since there are only non-line-of-sight components in the Tx-Rx subchannel, the corresponding space-time-frequency correlation function can be expressed as:

[0138]

[0139] like Figure 4 As shown in Figure 2, by deploying the optimized reflection phase on the IRS, the wireless channel amplitude can be effectively improved and the multipath effect of the channel can be reduced, which demonstrates the effectiveness of the proposed channel model.

[0140] By introducing an airborne IRS into a traditional vehicle-to-vehicle channel, a vehicle-to-vehicle channel model assisted by an airborne IRS was constructed. This model simulates the impulse response and channel statistics of the vehicle-to-vehicle channel assisted by an airborne IRS, and can be used to evaluate the performance of IRS communication systems. This addresses current shortcomings in IRS channel modeling, provides a new simulation method for analyzing IRS-assisted wireless channels, and can support the design and performance evaluation of IRS-assisted communication systems.

[0141] Example 2:

[0142] A system for implementing the above method includes:

[0143] The communication scenario unit is configured to: construct an IRS-assisted vehicle-to-vehicle communication scenario, with the transmitting and receiving stations each equipped with a linear array. The IRS is deployed on the drone and rotates in three-dimensional space with the movement of the drone, and a channel matrix is constructed based on the set scenario parameters;

[0144] The sub-channel unit is configured to: decompose the IRS communication channel in the channel matrix into a Tx-IRS sub-channel, an IRS-Rx sub-channel, and a Tx-Rx sub-channel, where Tx represents a transmitting end and Rx represents a receiving end, and construct channel transfer functions of the three sub-channels respectively;

[0145] The channel transfer function unit is configured to: construct a channel transfer function of the IRS auxiliary model based on the sub-channel transfer function obtained in the sub-channel unit;

[0146] The channel transfer function optimization unit is configured to: optimize the reflection phase of the IRS with the goal of maximizing the received power;

[0147] The channel simulation unit is configured to obtain a corresponding space-time-frequency correlation function based on the optimized channel transmission function.

[0148] By introducing an IRS carried by a drone into a traditional vehicle-to-vehicle communication scenario, an airborne IRS-assisted vehicle-to-vehicle communication scenario was constructed. This method can reflect the impact of path loss, IRS rotation angle, reflection unit pattern, and the flight altitude and speed of the drone on the statistical characteristics of the wireless channel. By optimizing the IRS phase, the IRS-assisted channel exhibits statistical characteristics similar to those of a direct path, and greatly reduces the channel's multipath fading and Doppler spread.

[0149] Example 3:

[0150] This embodiment provides a computer-readable storage medium having a computer program stored thereon. When the program is executed by a processor, the steps of the method for simulating an airborne IRS-assisted vehicle-to-vehicle communication channel as described in the first embodiment are implemented.

[0151] This method introduces a drone-mounted IRS into a traditional vehicle-to-vehicle communication scenario, creating an airborne IRS-assisted vehicle-to-vehicle communication scenario. This method reflects the impact of path loss, IRS rotation angle, reflection unit pattern, and the drone's flight altitude and speed on the statistical characteristics of the wireless channel. By optimizing the IRS phase, the IRS-assisted channel exhibits statistical characteristics similar to those of a direct path, significantly reducing the channel's multipath fading and Doppler spread.

[0152] Example 4:

[0153] This embodiment provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, the steps of the method for simulating an airborne IRS-assisted vehicle-to-vehicle communication channel as described in the first embodiment are implemented.

[0154] This method introduces a drone-mounted IRS into a traditional vehicle-to-vehicle communication scenario, creating an airborne IRS-assisted vehicle-to-vehicle communication scenario. This method reflects the impact of path loss, IRS rotation angle, reflection unit pattern, and the drone's flight altitude and speed on the statistical characteristics of the wireless channel. By optimizing the IRS phase, the IRS-assisted channel exhibits statistical characteristics similar to those of a direct path, significantly reducing the channel's multipath fading and Doppler spread.

[0155] The steps or modules involved in Examples 2 to 4 above correspond to those in Example 1. For detailed implementations, please refer to the relevant description of Example 1. The term "computer-readable storage medium" should be understood to mean a single medium or multiple media that includes one or more instruction sets; it should also be understood to include any medium that can store, encode, or carry an instruction set for execution by a processor and cause the processor to perform any method of the present invention.

[0156] The foregoing description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Those skilled in the art will readily appreciate that various modifications and variations of the present invention are possible. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present invention are intended to be within the scope of protection of the present invention.

Claims

1. A vehicle-to-vehicle communication channel simulation method assisted by airborne IRS, characterized in that: The following steps are involved: S1: Construct an IRS-assisted vehicle-to-vehicle communication scenario. The transmitting and receiving stations are equipped with linear arrays. The IRS is deployed on the drone and rotates in three-dimensional space with the movement of the drone. The channel matrix is constructed based on the set scenario parameters. S2: The IRS communication channel is decomposed into the Tx-IRS subchannel, the IRS-Rx subchannel, and the Tx-Rx subchannel, where Tx represents the transmitter and Rx represents the receiver. The channel transfer functions of the three subchannels are constructed respectively. S3: Based on the sub-channel transfer function obtained in S2, the channel transfer function of the IRS auxiliary model is constructed; S4: Optimize the IRS reflection phase with the goal of maximizing the received power; S5: Based on the channel transfer function optimized in S4, the corresponding space-time-frequency correlation function is obtained; The channel transfer function optimized based on S4 is used to obtain the corresponding space-time-frequency correlation function, which is shown in the following formula: in, is the time interval, is the frequency interval, is the space-time-frequency correlation function of the Tx-IRS subchannel, is the space-time-frequency correlation function of the Rx-IRS subchannel, is the space-time-frequency correlation function of the Tx-Rx subchannel, t is time, f is frequency, K is the number of IRS reflection units, is the amplitude of the kth reflection unit, represents the reflection phase shift of the kth reflection unit.

2. The airborne IRS-assisted vehicle-to-vehicle communication channel simulation method according to claim 1, characterized in that: In S1, the channel matrix is as follows: in, 、 and Represent the channel matrices of Tx-IRS, IRS-Rx and Tx-Rx subchannels respectively, is the reflection coefficient matrix of IRS, Convert the contained elements to a diagonal matrix, and represent the amplitude and phase shift of the kth reflection unit respectively.

3. The airborne IRS-assisted vehicle-to-vehicle communication channel simulation method according to claim 1, characterized in that: In S2, at time t ,frequency f At the p The first transmitting antenna q The channel transfer function of the root receiving antenna is expressed as follows: in, is the channel transfer function of the Tx-IRS subchannel, that is, the channel transfer function between the p-th transmitting antenna and the k-th reflector unit; is the channel transfer function of the IRS-Rx subchannel, that is, the channel transfer function between the kth reflection unit and the qth receiving antenna; is the channel transfer function of the Tx-Rx subchannel, that is, the channel transfer function between the pth transmitting antenna and the qth receiving antenna without passing through the IRS, K is the number of IRS reflection units, is the amplitude of the kth reflection unit, represents the reflection phase shift of the kth reflection unit.

4. The airborne IRS-assisted vehicle-to-vehicle communication channel simulation method according to claim 3, characterized in that: In the channel transfer function of the Tx-IRS subchannel, The transmitting antenna and The directional patterns of the IRS reflection units are respectively and Represented by, where the directivity pattern of the IRS reflector unit is as follows: in, is the angle between the IRS normal and the arrival ray.

5. The airborne IRS-assisted vehicle-to-vehicle communication channel simulation method according to claim 1, characterized in that: The IRS rotates with the drone in the air, and the local coordinates after rotation are shown as follows: in, are the rotation angles of IRS around the x, y, and z axes, respectively.

6. The airborne IRS-assisted vehicle-to-vehicle communication channel simulation method according to claim 1, characterized in that: In S4, the optimized IRS reflection phase is as follows: in, and are the Doppler frequencies of the line-of-sight components in the Tx-IRS and IRS-Rx subchannels, and are the delays of the line-of-sight components in the Tx-IRS and IRS-Rx subchannels, is the system carrier frequency, is the wavelength, is the local coordinate of the kth reflection unit, t is time, f is frequency, K is the number of IRS reflection units, is the amplitude of the kth reflection unit.

7. Airborne IRS-assisted vehicle-to-vehicle communication channel simulation system, characterized by: include: The communication scenario unit is configured to: construct an IRS-assisted vehicle-to-vehicle communication scenario, with the transmitting and receiving stations each equipped with a linear array. The IRS is deployed on the drone and rotates in three-dimensional space with the movement of the drone, and a channel matrix is constructed based on the set scenario parameters; The sub-channel unit is configured to: decompose the IRS communication channel into a Tx-IRS sub-channel, an IRS-Rx sub-channel, and a Tx-Rx sub-channel, where Tx represents a transmitting end and Rx represents a receiving end, and construct channel transfer functions of the three sub-channels respectively; The channel transfer function unit is configured to: construct a channel transfer function of the IRS auxiliary model based on the sub-channel transfer function obtained in the sub-channel unit; The channel transfer function optimization unit is configured to: optimize the reflection phase of the IRS with the goal of maximizing the received power; The channel simulation unit is configured to: obtain a corresponding space-time-frequency correlation function based on the optimized channel transfer function; The corresponding space-time-frequency correlation function is obtained based on the optimized channel transfer function, and the obtained space-time-frequency correlation function is shown in the following formula: in, is the time interval, is the frequency interval, is the space-time-frequency correlation function of the Tx-IRS subchannel, is the space-time-frequency correlation function of the Rx-IRS subchannel, is the space-time-frequency correlation function of the Tx-Rx subchannel, t is time, f is frequency, K is the number of IRS reflection units, is the amplitude of the kth reflection unit, represents the reflection phase shift of the kth reflection unit.

8. A computer-readable storage medium, characterized in that A computer program is stored thereon, and when the program is executed by a processor, the steps in the airborne IRS-assisted vehicle-to-vehicle communication channel simulation method as described in any one of claims 1 to 6 are implemented.

9. A computer device, characterized in that: The invention comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the steps in the method for simulating an airborne IRS-assisted vehicle-to-vehicle communication channel as claimed in any one of claims 1 to 6 are implemented.

Images