Method for establishing millimeter wave channel model for UAV based on modular intelligent reflective surface

Abstract

The present invention discloses a method for establishing a millimeter-wave channel model for unmanned aerial vehicles (UAVs) based on modular intelligent reflective surfaces. The method comprises the following steps: establishing a near-field UAV millimeter-wave channel model assisted by an intelligent reflective surface to obtain its complex channel gain; establishing a near-field UAV millimeter-wave channel model with modular intelligent reflective surfaces to obtain its complex channel gain; simplifying the near-field UAV millimeter-wave channel model based on modular intelligent reflective surfaces to establish a far-field channel model to obtain its complex channel gain; designing the reflection phase of the modular intelligent reflective surface based on the maximization criterion of the reflective unit gain of the far-field channel model; calculating an approximate closed-form expression for the received signal power; and calculating the power loss ratio to explore the impact of the intelligent reflective surface partitioning scheme on the performance gain of the UAV millimeter-wave system. The method of the present invention can provide ideas for exploring the application prospects and exploration of modular intelligent reflective surfaces in UAV millimeter-wave communication systems, and provide more possibilities for next-generation wireless communication technologies.

Description

Technical Field

[0001] The present invention relates to wireless communication technology, and in particular to a method for establishing a millimeter wave channel model of an unmanned aerial vehicle based on modularization of intelligent reflecting surfaces. Background Art

[0002] The advent of the 5G era has ushered in a series of technological revolutions, and 5G-related research and applications are constantly emerging. Smart reflectors, consisting of two-dimensional planes composed of low-cost passive reflective elements, are an emerging technology considered a reliable solution for improving channel performance and widely considered a key technology for future 6G mobile communications. Each reflector element in a smart reflector can independently control the amplitude or phase of the incident signal, enabling efficient signal transmission. Controlled by an external controller, the smart reflector can freely adjust the reflected phase shift based on the incident signal to maximize spectrum utilization. Therefore, establishing an accurate and appropriate channel model can provide a theoretical basis for the design of wireless communication systems assisted by smart reflectors, thereby improving the channel transmission environment. Millimeter waves, offering a very large frequency range, are also considered a key factor in significantly improving communication quality in the future.

[0003] In existing public technical content, the MIMO channel model containing smart reflective surfaces is comparable to the large-scale MIMO channel model without smart reflective surfaces; by adjusting the reflection phase in real time, the impact of multipath fading caused by the movement of the transmitter and receiver can be reduced or even offset, and the signal reception power can be increased; some studies have shown that only when smart reflective surfaces are placed around the transmitter and receiver will they have a significant impact on the channel, and some studies have found that wireless communication systems assisted by smart reflective surfaces not only have higher data rates than deploying repeaters, but also reduce costs; some research results indicate that the reflection phase of smart reflective surfaces in the near-field area needs to be reconsidered.

[0004] Existing technologies include the paper "Channel estimation for extremely large-scale MIMO: Far-field or near-field?" by M. Cui and L. Dai, "IEEE Trans. Commun., vol. 70, no. 4, pp. 2663-2677, April 2022." This study shows that when antennas are large enough, plane waves cannot accurately simulate the propagation characteristics of electromagnetic waves. Therefore, spherical waves should be used instead of plane waves to model the channel model of extremely large-scale MIMO communication systems. W. Tang, X. Chen, M. Z. Chen, J. Y. Dai, Y. Han, M. D. Renzon, S. Jin, Q. Cheng, and T. J. Cui, “Path loss modeling and measurements for reconfigurable intelligent surface in millimeter-wave frequency band,” IEEE Trans. Commun., vol. 70, no. 9, pp. 6259-6276, Sep. 2022, establishes a path loss model for a millimeter-wave near-field system assisted by a smart reflector and designs the reflection phase of the smart reflector. However, this reflection phase requires the precise distance between each smart reflector unit and the transceiver antenna unit. For passively reflecting smart reflectors, this precise distance between the smart reflector unit and the transceiver is difficult to achieve. H. Jiang, B. Xiong, H. Zhang, and E. Basar's paper "Hybrid far- and near-field modeling for reconfigurable intelligent surface assisted V2V channels: A sub-array partition based approach," IEEE Trans. Wireless. Commun., vol. 22, no. 11, pp. 8290-8303, Nov. 2023, uses intelligent reflective surface partitioning to establish a vehicle-to-vehicle channel model to reduce the complexity of near-field system modeling. However, this model ignores the reflection phase of the intelligent reflective unit.

[0005] In summary, UAV millimeter-wave channel modeling based on modular intelligent reflectors is in its initial stages, and the statistical characteristics of the UAV channel using the intelligent reflector block scheme (IRS) remain to be explored. Therefore, a UAV millimeter-wave channel model based on modular intelligent reflectors is necessary. The establishment of this model can provide a basis for future system performance analysis and precoding algorithm design. Summary of the Invention

[0006] Purpose of the invention: The purpose of the present invention is to provide an accurate method for establishing a UAV millimeter-wave channel model based on modular intelligent reflective surfaces. This model establishment method can provide strong support for the exploration of key technologies of 6G communication systems.

[0007] Technical solution: The method for establishing a UAV millimeter wave channel model based on modular intelligent reflective surfaces of the present invention comprises the following steps:

[0008] S1. A UAV millimeter wave communication system assisted by an intelligent reflecting surface is established, and a UAV millimeter wave near-field channel model assisted by an intelligent reflecting surface is established, and the complex channel gain of the UAV millimeter wave near-field channel model assisted by an intelligent reflecting surface is obtained;

[0009] S2. Divide the smart reflective surface into multiple identical submodules and renumber the reflective units within each submodule to establish a UAV millimeter-wave near-field channel model based on the modularization of the smart reflective surface. Obtain the complex channel gain of the UAV millimeter-wave near-field channel model based on the modularization of the smart reflective surface.

[0010] S3. Simplify the UAV millimeter-wave near-field channel model based on the modularization of the intelligent reflecting surface in step S2, use plane waves instead of spherical waves to simulate the propagation characteristics of electromagnetic waves, establish a UAV millimeter-wave far-field channel model based on the modularization of the intelligent reflecting surface, and obtain the complex channel gain of the far-field channel model; design the reflection phase of the modularized intelligent reflecting surface based on the maximization criterion of the reflection unit gain of the far-field channel model, and the designed reflection phase includes the reflection phase related to the reflection unit and the reflection phase related to the sub-module; the reflection phase related to the reflection unit is determined by the plane wave assumption, and the reflection phase related to the sub-module is determined by the spherical wave assumption;

[0011] S4. Using the reflection phase of the designed modularized smart reflector, solve the approximate closed-form expression of the received signal power of the UAV millimeter-wave near-field channel model based on the modularized smart reflector;

[0012] S5. Based on the obtained approximate closed-form expression of the received signal power, the reflection phase after modularization of the designed smart reflector is used to calculate the power loss ratio of the UAV millimeter-wave near-field channel model based on the modularization of the smart reflector. Using the obtained power loss ratio, the impact of the smart reflector block scheme on the performance gain of the UAV millimeter-wave system is explored.

[0013] Furthermore, the complex channel gain h of the UAV millimeter wave near-field channel model based on the intelligent reflector in step S1 is 1,p Expressed as:

[0014]

[0015] Where π represents the circumference of a circle, δ1 and δ2 represent the spacing between adjacent row and column reflective units on the smart reflective surface, λ represents the wavelength of the electromagnetic wave emitted by the drone, N1 and N2 are the number of row and column reflective units on the smart reflective surface, and γ a and γ d They represent the path losses from the UAV to the smart reflective surface and from the smart reflective surface to the receiving end, It represents the projection of the electromagnetic wave emitted by the drone on the normal line of the smart reflective surface. represents the projection of the electromagnetic wave signal reflected by the smart reflective surface on the normal line of the smart reflective surface, e represents the exponential function, represents the distance from the pth transmitting antenna of the drone to the (n2,n1)th reflecting unit, Indicates the distance from the (n2, n1)th reflector unit to the receiving antenna, Represents the reflection phase of the (n2, n1)th reflection unit on the smart reflection surface.

[0016] Furthermore, the complex channel gain h of the UAV millimeter wave near-field channel model with modular intelligent reflective surface in step S2 is 2,p Expressed as:

[0017]

[0018] Where π represents the circumference of a circle, δ1 and δ2 represent the spacing between adjacent row and column reflection units on the smart reflective surface, λ represents the wavelength of the electromagnetic wave emitted by the drone, and γ a and γ d They represent the path losses from the UAV to the smart reflective surface and from the smart reflective surface to the receiving end, It represents the projection of the electromagnetic wave emitted by the drone on the normal line of the smart reflective surface. represents the projection of the electromagnetic wave signal reflected by the smart reflective surface on the normal line of the smart reflective surface, Q represents the number of submodules of the smart reflective surface, q represents the subscript index of the submodule of the smart reflective surface, M1 and M2 represent the number of row reflective units and column reflective units in each submodule respectively, m1 and m2 represent the subscript index of the row reflective unit and column reflective unit in each submodule, e represents the exponential function, is the reflection phase of the qth submodule, It represents the distance from the pth transmitting antenna of the UAV to the (m2, m1)th reflector unit in the qth submodule. Represents the distance from the receiving antenna to the (m2, m1)th reflector unit in the qth submodule.

[0019] Furthermore, the complex channel gain h of the UAV millimeter wave far-field channel model based on the intelligent reflector modularization established in step S3 is 3,p , expressed as:

[0020]

[0021] Where π represents the circumference of a circle, δ1 and δ2 represent the spacing between adjacent row and column reflection units on the smart reflective surface, λ represents the wavelength of the electromagnetic wave emitted by the drone, and γ a and γ d They represent the path losses from the UAV to the smart reflective surface and from the smart reflective surface to the receiving end, It represents the projection of the electromagnetic wave emitted by the drone on the normal line of the smart reflective surface. represents the projection of the electromagnetic wave signal reflected by the smart reflective surface on the normal line of the smart reflective surface, Q represents the number of submodules of the smart reflective surface, q represents the subscript index of the submodule of the smart reflective surface, M1 and M2 represent the number of row reflective units and column reflective units in each submodule respectively, m1 and m2 represent the subscript index of the row reflective unit and column reflective unit in each submodule, e represents the exponential function, is the reflection phase of the qth submodule, and represents the auxiliary variable, p represents the subscript index of the transmitting antenna unit, P represents the number of transmitting antenna units, δ represents the distance between adjacent transmitting antenna units, Ψ a Represents the angle between the line connecting the drone to the center of the intelligent reflective surface and the positive direction of the x-axis, ε a,q represents the distance from the UAV to the center of the qth submodule on the intelligent reflective surface, ε d,q represents the distance from the receiving antenna to the center of the qth submodule on the smart reflector, Φ a,q represents the angle between the line connecting the drone and the center of the qth submodule of the intelligent reflective surface and the positive direction of the x-axis, Φ d,qΩ represents the angle between the line connecting the receiving antenna to the center of the qth submodule of the smart reflector and the positive direction of the x-axis. a,q Ω represents the angle between the line connecting the drone and the center of the qth submodule on the intelligent reflector and the positive direction of the z-axis, d,q It represents the angle between the line connecting the receiving antenna to the center of the qth submodule of the smart reflector and the positive direction of the z-axis.

[0022] Furthermore, based on the maximization criterion of the reflection unit gain of the UAV millimeter-wave far-field channel model under the modular solution, the reflection phase of the modularized smart reflector is designed, including:

[0023] Complex channel gain h of the UAV millimeter-wave far-field channel model based on the modularization of the smart reflector 3,p , the reflection unit gain g(Q,M1,M2) of the smart reflector is expressed as:

[0024]

[0025] In order to achieve the maximum reflective unit gain of the smart reflector, the modular reflection phase of the smart reflector is expressed as:

[0026]

[0027] Among them, α q represents the constant phase associated with submodule q, represents the expected angle between the line connecting the drone and the center of the qth submodule of the intelligent reflector and the positive direction of the x-axis, It represents the expected angle between the line connecting the receiving antenna to the center of the qth submodule of the smart reflector and the positive direction of the x-axis. represents the expected angle between the line connecting the drone and the center of the qth submodule on the intelligent reflector and the positive direction of the z-axis, represents the expected angle between the line connecting the receiving antenna to the center of the qth submodule of the smart reflector and the positive direction of the z-axis; Substituting the reflection unit gain g(Q,M1,M2), we have:

[0028]

[0029] Among them, sin represents the sine function, θ q , △1 and △2 represent auxiliary variables, which are expressed as:

[0030]

[0031] According to the reflection unit gain, when △1=0, △2=0 and When , the reflection unit gain g(Q,M1,M2) has a maximum value g(Q,M1,M2)=QM1M2; and α q The following conditions are met:

[0032] At this time, and α q Substitute θ m1m2,q The modular reflection phase of the designed smart reflector is expressed as:

[0033]

[0034] Furthermore, step S4 includes:

[0035] S41, using the second-order Taylor approximation, the distance from the transmitter to the (m2, m1)th reflector unit of the qth submodule The distance from the receiving end to the (m2, m1)th reflector unit of the qth submodule It can be expressed approximately as:

[0036]

[0037] Among them, ε a,q represents the distance from the UAV to the center of the qth submodule on the intelligent reflective surface, ε d,q represents the distance from the receiving antenna to the center of the qth submodule on the smart reflector, Ψ a represents the angle between the line connecting the UAV to the center of the smart reflective surface and the positive direction of the x-axis, δ represents the spacing between adjacent antenna units at the transmitting end, δ1 and δ2 represent the spacing between adjacent row reflective units and adjacent column reflective units on the smart reflective surface, respectively. and represents an auxiliary variable, p represents the subscript index of the transmitting antenna unit, P represents the number of transmitting antenna units, M1 and M2 represent the number of row reflection units and column reflection units in each submodule respectively, m1 and m2 represent the subscript index of the row reflection unit and column reflection unit in each submodule, Φ a,q represents the angle between the line connecting the drone and the center of the qth submodule of the intelligent reflective surface and the positive direction of the x-axis, Φ d,q Ω represents the angle between the line connecting the receiving antenna to the center of the qth submodule of the smart reflector and the positive direction of the x-axis. a,q Ω represents the angle between the line connecting the drone and the center of the qth submodule on the intelligent reflector and the positive direction of the z-axis, d,q It represents the angle between the line connecting the receiving antenna to the center of the qth submodule of the smart reflector and the positive direction of the z-axis;

[0038] S42, the approximate distance and After substituting the reflection phase designed in step S3 into the complex channel gain of the UAV millimeter wave near-field channel model with modular intelligent reflector in step S2, the received signal power is expressed as:

[0039]

[0040] Among them, P r is the received signal power, It represents the projection of the electromagnetic wave emitted by the drone on the normal line of the smart reflective surface. represents the projection of the electromagnetic wave signal reflected by the smart reflective surface on the normal line of the smart reflective surface, ε a represents the distance from the drone to the center of the smart reflective surface, ε d represents the distance from the receiving antenna to the center of the smart reflector, Q represents the number of submodules of the smart reflector, q represents the subscript index of the submodule of the smart reflector, f(η1,η2) is an auxiliary variable, is represented as an auxiliary variable, It is represented as an auxiliary variable, λ represents the wavelength of the electromagnetic wave emitted by the UAV;

[0041] S43, because and The auxiliary variables f(η1,η2) are expressed as:

[0042]

[0043] Among them, x and y are integration variables;

[0044] S44, make f(η1,η2) is further expressed as:

[0045]

[0046] Among them, t and τ are integration variables;

[0047] S45. Using the Fresnel integral function, the received signal power is approximately expressed as:

[0048]

[0049] Among them, P t represents the transmitted signal power, C(·) and S(·) are Fresnel functions, and Represented as auxiliary variables.

[0050] Furthermore, in step S5, the power loss ratio Γ of the UAV millimeter wave near-field channel model based on the modular intelligent reflector is:

[0051]

[0052] Where Q represents the number of submodules of the smart reflective surface, q represents the subscript index of the submodule of the smart reflective surface, C(·) and S(·) represent Fresnel functions, and is represented as auxiliary variables, M1 and M2 represent the number of row reflection units and column reflection units in each submodule respectively, δ1 and δ2 represent the spacing between adjacent row reflection units and adjacent column reflection units on the smart reflection surface respectively, η1 and η2 are represented as auxiliary variables, and λ represents the wavelength of the electromagnetic wave emitted by the UAV.

[0053] The system corresponding to the method includes:

[0054] A complex channel gain calculation unit is used for the UAV millimeter wave communication system assisted by the intelligent reflecting surface, establishes a UAV millimeter wave near-field channel model assisted by the intelligent reflecting surface, and obtains the complex channel gain of the UAV millimeter wave near-field channel model assisted by the intelligent reflecting surface;

[0055] A post-modular complex channel gain calculation unit is used to divide the smart reflective surface into multiple identical sub-modules, renumber the reflective units within each sub-module, establish a UAV millimeter-wave near-field channel model based on the modularization of the smart reflective surface, and obtain the complex channel gain of the UAV millimeter-wave near-field channel model based on the modularization of the smart reflective surface;

[0056] The reflection phase design unit is used to simplify the UAV millimeter-wave near-field channel model based on the modularization of the intelligent reflector surface. Plane waves are used instead of spherical waves to simulate the propagation characteristics of electromagnetic waves. The millimeter-wave far-field channel model of the UAV based on the modularization of the intelligent reflector surface is established to obtain the complex channel gain of the far-field channel model. The reflection phase of the modularized intelligent reflector surface is designed based on the maximization criterion of the reflector unit gain of the far-field channel model. The designed reflection phase includes the reflection phase related to the reflector unit and the reflection phase related to the submodule. The reflection phase related to the reflector unit is determined by the plane wave assumption, and the reflection phase related to the submodule is determined by the spherical wave assumption.

[0057] The received signal power approximation unit is used to solve the approximate closed-form expression of the received signal power of the UAV millimeter-wave near-field channel model based on the modularization of the smart reflector by using the reflection phase of the designed smart reflector;

[0058] The power loss ratio calculation unit is used to calculate the power loss ratio of the UAV millimeter wave near-field channel model based on the modularization of the smart reflector according to the obtained approximate closed-form expression of the received signal power and the reflection phase of the designed smart reflector after modularization; using the obtained power loss ratio, the influence of the smart reflector blocking scheme on the performance gain of the UAV millimeter wave system is explored.

[0059] An electronic device for storing and executing the method, the device comprising:

[0060] a memory storing executable program code;

[0061] a processor coupled to the memory;

[0062] The processor calls the executable program code stored in the memory to execute the steps of the method for establishing a UAV millimeter wave channel model based on intelligent reflecting surface modularization.

[0063] A computer-readable storage medium for storing and executing the method, wherein the computer-readable storage medium stores computer instructions, and when the computer instructions are called, they are used to execute the steps of the method for establishing a UAV millimeter wave channel model based on modular intelligent reflecting surfaces.

[0064] Beneficial effects: Compared with the prior art, the significant technical effects of the present invention are: in order to reduce the complexity of the UAV millimeter-wave near-field channel model based on the assistance of intelligent reflecting surfaces, the present invention constructs a modular UAV millimeter-wave near-field channel model of the intelligent reflecting surface and obtains its complex channel gain function; a composite near-field and far-field reflection phase is designed under the condition of the maximization criterion of the intelligent reflecting unit gain function; at the same time, the present invention takes into account the influence of the number and size of the reflecting units of the intelligent reflecting surface on the channel receiving signal power and performance gain of the cellular system; therefore, the present invention can better explore the influence of the intelligent reflecting surface blocking on the performance gain of the UAV millimeter-wave system. BRIEF DESCRIPTION OF THE DRAWINGS

[0065] Figure 1 Flow chart of the method of the present invention;

[0066] Figure 2 Schematic diagram of the millimeter-wave near-field channel model for UAVs assisted by intelligent reflective surfaces;

[0067] Figure 3 A schematic diagram comparing the near-field channel model proposed in the present invention and the traditional far-field channel model;

[0068] Figure 4 This is a schematic diagram comparing the received signal power between the designed reflection phase and the ideal reflection phase under the intelligent reflector block solution;

[0069] Figure 5 Schematic diagram of the power loss ratio of the UAV millimeter wave system under different smart reflector block schemes. DETAILED DESCRIPTION

[0070] The present invention is described in detail below with reference to the accompanying drawings and specific embodiments. The following examples will help those skilled in the art further understand the present invention, but are not intended to limit the present invention in any form. It should be noted that those skilled in the art may make several changes and modifications without departing from the scope of the present invention. These all fall within the scope of protection of the present invention.

[0071] The present invention provides a method for establishing a UAV millimeter wave channel model based on the modularization of an intelligent reflecting surface, comprising: establishing a UAV millimeter wave near-field channel model assisted by an intelligent reflecting surface, and obtaining the complex channel gain of the UAV millimeter wave near-field channel model; obtaining the complex channel gain of the UAV millimeter wave near-field channel model of the intelligent reflecting surface modularization based on the intelligent reflecting surface; designing the reflection phase of the intelligent reflecting surface, wherein the reflection phase of the intelligent reflecting surface is composed of the reflection phase related to the reflection unit and the reflection phase related to the module; utilizing the designed reflection phase to obtain an approximate closed-form expression for the received signal power of the UAV millimeter wave near-field channel model of the intelligent reflecting surface modularization; and designing a power loss ratio to reflect the influence of the designed reflection phase of the intelligent reflecting surface on the received signal power. The method of the present invention can provide ideas for exploring the application prospects and exploration of the modularization of intelligent reflecting surfaces in UAV millimeter wave communication systems, and provide more possibilities for the next generation of wireless communication technologies.

[0072] like Figure 1 As shown, the method for establishing a UAV millimeter wave channel model based on intelligent reflective surface modularization of the present invention includes the following steps:

[0073] S1. Considering the UAV millimeter wave communication system assisted by the intelligent reflective surface, the transmitting end is a uniform linear antenna array, which is deployed at the bottom of the UAV end, and the receiving end is a single antenna user. The direct link between the transmitter and the receiver is blocked by the ground buildings. The intelligent reflective surface is deployed on the surface of the building, and its main function is to establish a virtual direct link between the transmitter and the receiver. When the intelligent reflective surface is used to assist millimeter wave communication, the receiver and the transmitter are in the near field area of ​​the intelligent reflective surface. Figure 2 As shown, the present invention first establishes a UAV millimeter wave near-field channel model based on the assistance of an intelligent reflector, and obtains the complex channel gain of the established UAV millimeter wave near-field channel model. The complex channel gain h 1,p It is expressed as follows:

[0074]

[0075] Where π represents the circumference of a circle and is taken as 3.14. δ1 and δ2 represent the spacing between adjacent row and column reflective units on the smart reflective surface, respectively. λ represents the wavelength of the electromagnetic wave emitted by the drone. N1 and N2 are the numbers of row and column reflective units on the smart reflective surface, respectively. γa and γ d They represent the path losses from the UAV to the smart reflective surface and from the smart reflective surface to the receiving end, It represents the projection of the electromagnetic wave emitted by the drone on the normal line of the smart reflective surface. represents the projection of the electromagnetic wave signal reflected by the smart reflective surface on the normal line of the smart reflective surface, e represents the exponential function, represents the distance from the pth transmitting antenna of the drone to the (n2,n1)th reflecting unit, Indicates the distance from the (n2, n1)th reflector unit to the receiving antenna, Represents the reflection phase of the (n2, n1)th reflection unit on the smart reflection surface.

[0076] S2. In the UAV millimeter-wave near-field channel model assisted by the intelligent reflecting surface in step S1, the reflection phase design of the intelligent reflecting surface needs to obtain the precise distance between the transceiver and each reflection unit. Since there is no sensor equipment deployed on the passive intelligent reflecting surface, it is impossible to obtain the precise distance between the transceiver and each reflection unit on the intelligent reflecting surface through channel estimation. Therefore, the present invention divides the intelligent reflecting surface into multiple identical sub-modules, and renumbers the reflection units in each sub-module. On the basis of step S1, a UAV millimeter-wave near-field channel model based on the modularization of the intelligent reflecting surface is established, and the complex channel gain of the near-field channel model is obtained. The complex channel gain function in step S2 is equivalent to the complex channel gain function of the UAV millimeter-wave near-field channel model in step S1. The complex channel gain h of the UAV millimeter-wave near-field channel model with modularization of the intelligent reflecting surface 2,p It can be expressed as:

[0077]

[0078] Where Q represents the number of submodules of the smart reflective surface, M1 and M2 represent the number of row reflective units and column reflective units in each submodule, respectively, and m1 and m2 represent the subscript indices of the row reflective units and column reflective units in each submodule. It represents the distance from the pth transmitting antenna of the UAV to the (m2, m1)th reflector unit in the qth submodule. Indicates the distance from the receiving antenna to the (m2, m1)th reflector unit in the qth submodule, is the reflection phase of the qth submodule.

[0079] S3. The reflection phase design of the modularized smart reflective surface in step S2 still needs to obtain the precise distance between the transceiver and each smart reflective unit. Therefore, in order to reduce the complexity of the modeling of the UAV millimeter wave system by the modularized solution of the smart reflective surface, the present invention designs a composite near-field and far-field reflection phase. First, the present invention simplifies the UAV millimeter wave near-field channel model of the modularized smart reflective surface in step S2, uses plane waves instead of spherical waves to simulate the propagation characteristics of electromagnetic waves, establishes a UAV millimeter wave far-field channel model based on the modularization of the smart reflective surface, and obtains the complex channel gain of the UAV millimeter wave far-field channel model under the modularization scheme. Secondly, the reflection phase of the modularized smart reflective surface is designed based on the maximization criterion of the reflection unit gain of the UAV millimeter wave far-field channel model under the modularization scheme. The designed reflection phase consists of two parts: the reflection phase related to the reflection unit and the reflection phase related to the sub-module. The reflection phase related to the reflection unit is determined by the plane wave assumption, and it is only necessary to obtain the angle of the transceiver relative to the center of each sub-module. The reflection phase associated with each submodule is determined by the spherical wave assumption, requiring only the propagation distance of the transceiver relative to the center of each module. Therefore, the composite near-field and far-field reflection phases designed in this invention do not require the precise distance between the transceiver and each intelligent reflector unit. This reflection phase is easily achievable for intelligent reflective surfaces. Specifically, this includes:

[0080] S31, complex channel gain h of the simplified far-field channel model 3,p It can be expressed as:

[0081]

[0082] in, and represents the auxiliary variable, p represents the subscript index of the transmitting antenna unit, P represents the number of transmitting antenna units, δ represents the distance between adjacent transmitting antenna units, Ψ a Represents the angle between the line connecting the drone to the center of the intelligent reflective surface and the positive direction of the x-axis, ε a,q represents the distance from the UAV to the center of the qth submodule on the intelligent reflective surface, ε d,q represents the distance from the receiving antenna to the center of the qth submodule on the smart reflector, Φ a,q represents the angle between the line connecting the drone and the center of the qth submodule of the intelligent reflective surface and the positive direction of the x-axis, Φ d,q Ω represents the angle between the line connecting the receiving antenna to the center of the qth submodule of the smart reflector and the positive direction of the x-axis. a,q Ω represents the angle between the line connecting the drone and the center of the qth submodule on the intelligent reflector and the positive direction of the z-axis, d,q It represents the angle between the line connecting the receiving antenna to the center of the qth submodule of the smart reflector and the positive direction of the z-axis.

[0083] S32, based on the complex channel gain h in step S31 2,p , the reflection unit gain of the smart reflection surface can be written as:

[0084]

[0085] Wherein, g(Q,M1,M2) is the reflection unit gain of the smart reflector;

[0086] In order to achieve the maximum reflective unit gain of the smart reflector, the present invention assumes that the modular reflective phase of the smart reflector can be expressed as:

[0087]

[0088] Among them, α q represents the constant phase associated with submodule q, represents the expected angle between the line connecting the drone and the center of the qth submodule of the intelligent reflector and the positive direction of the x-axis, It represents the expected angle between the line connecting the receiving antenna to the center of the qth submodule of the smart reflector and the positive direction of the x-axis. represents the expected angle between the line connecting the drone and the center of the qth submodule on the intelligent reflector and the positive direction of the z-axis, Represents the expected angle between the line connecting the receiving antenna to the center of the qth submodule of the smart reflector and the positive direction of the z-axis. Substituting the reflection unit gain g(Q,M1,M2), we have:

[0089]

[0090] Among them, sin represents the sine function, θ q , △1 and △2 represent auxiliary variables, which can be expressed as:

[0091]

[0092] According to the reflection unit gain, when △1=0, △2=0 and When , the reflection unit gain g(Q,M1,M2) reaches its maximum value g(Q,M1,M2)=QM1M2. and α q The following conditions are met:

[0093]

[0094] At this time, and α q Substitution The reflection phase of the designed submodule is:

[0095]

[0096] From the above formula, we can see that the reflection phase of the designed submodule is It consists of two parts: the reflection phase related to the reflection unit and the reflection phase related to the module. The reflection phase related to the reflection unit is determined by the plane wave assumption. It only needs to obtain the angle of the transceiver relative to the center of each submodule, such as Φ a,q , Φ d,q ,Ω a,q and Ω d,q The module-related reflection phase is determined by the spherical wave assumption. It is only necessary to obtain the propagation distance of the transceiver relative to the center of each submodule, such as ε a,q and ε d,q .

[0097] S4, using the designed composite near-field and far-field reflection phase Explore the approximate closed-form expression for the received signal power of the UAV millimeter-wave near-field channel model based on modular smart reflectors;

[0098] S41, using the second-order Taylor approximation, the distance from the transmitter to the (m2, m1)th reflector unit of the qth submodule The distance from the receiving end to the (m2, m1)th reflector unit of the qth submodule It can be approximately expressed as:

[0099]

[0100] S42, the approximate distance and The reflection phase of the submodule designed in step S3 is substituted into the complex channel gain h of the UAV millimeter wave near-field channel model with intelligent reflector modularization in step S2. 2,p After that, the received signal power is expressed as:

[0101]

[0102] Among them, P r is the received signal power, ε a represents the distance from the drone to the center of the smart reflective surface, ε d represents the distance from the receiving antenna to the center of the smart reflector, f(η1,η2) is an auxiliary variable, is represented as an auxiliary variable, Represented as auxiliary variables.

[0103] S43, because and The auxiliary variable f(η1,η2) can be expressed as:

[0104]

[0105] Where x and y are the integration variables.

[0106] S44, make f(η1,η2) can be further expressed as:

[0107]

[0108] Where t and τ are integration variables.

[0109] S45. Using the Fresnel integral function, the received signal power can be approximately expressed as:

[0110]

[0111] Among them, P t represents the transmitted signal power, C(·) and S(·) are Fresnel functions, and Represented as auxiliary variables.

[0112] S5. Based on the obtained approximate expression of the received signal power, the designed reflection phase is adopted and the power loss ratio Γ of the UAV millimeter wave near-field channel model based on the modular intelligent reflector surface is:

[0113]

[0114] The obtained power loss ratio is used to explore the impact of the smart reflector segmentation scheme on the performance gain of the UAV millimeter wave system.

[0115] The system corresponding to the method includes:

[0116] A complex channel gain calculation unit is used for the UAV millimeter wave communication system assisted by the intelligent reflecting surface, establishes a UAV millimeter wave near-field channel model assisted by the intelligent reflecting surface, and obtains the complex channel gain of the UAV millimeter wave near-field channel model assisted by the intelligent reflecting surface;

[0117] A post-modular complex channel gain calculation unit is used to divide the smart reflective surface into multiple identical sub-modules, renumber the reflective units within each sub-module, establish a UAV millimeter-wave near-field channel model based on the modularization of the smart reflective surface, and obtain the complex channel gain of the UAV millimeter-wave near-field channel model based on the modularization of the smart reflective surface;

[0118] The reflection phase design unit is used to simplify the UAV millimeter-wave near-field channel model based on the modularization of the intelligent reflector surface. Plane waves are used instead of spherical waves to simulate the propagation characteristics of electromagnetic waves. The millimeter-wave far-field channel model of the UAV based on the modularization of the intelligent reflector surface is established to obtain the complex channel gain of the far-field channel model. The reflection phase of the modularized intelligent reflector surface is designed based on the maximization criterion of the reflector unit gain of the far-field channel model. The designed reflection phase includes the reflection phase related to the reflector unit and the reflection phase related to the submodule. The reflection phase related to the reflector unit is determined by the plane wave assumption, and the reflection phase related to the submodule is determined by the spherical wave assumption.

[0119] The received signal power approximation unit is used to solve the approximate closed-form expression of the received signal power of the UAV millimeter-wave near-field channel model based on the modularization of the smart reflector by using the reflection phase of the designed smart reflector;

[0120] The power loss ratio calculation unit is used to calculate the power loss ratio of the UAV millimeter wave near-field channel model based on the modularization of the smart reflector according to the obtained approximate closed-form expression of the received signal power and the reflection phase of the designed smart reflector after modularization; using the obtained power loss ratio, the influence of the smart reflector blocking scheme on the performance gain of the UAV millimeter wave system is explored.

[0121] An electronic device for storing and executing the method, the device comprising:

[0122] a memory storing executable program code;

[0123] a processor coupled to the memory;

[0124] The processor calls the executable program code stored in the memory to execute the steps of the method for establishing a UAV millimeter wave channel model based on intelligent reflecting surface modularization.

[0125] A computer-readable storage medium for storing and executing the method, wherein the computer-readable storage medium stores computer instructions, and when the computer instructions are called, they are used to execute the steps of the method for establishing a UAV millimeter wave channel model based on modular intelligent reflecting surfaces.

[0126] Figure 3The figure shows a comparison of the received signal power of the near-field model proposed by the present invention and the traditional far-field model. When the size of the smart reflective surface reaches 180*180 and 240*240, the received signal power under the model proposed by the present invention is 4.9dBm and 9.9dBm higher. However, when the size of the smart reflective surface is 80*80, the advantage of the model of the present invention is not obvious. This is because when the size is small, the Rayleigh distance distinguishing the near and far fields is also small. When the size becomes larger, the original far-field area will be transformed into the respective near-field areas.

[0127] Figure 4 The figure shows a comparison between the received signal power calculated by the reflection phase designed by the present invention and the optimal received signal power. It can be seen that when the sizes of the smart reflection surface are 80*80, 180*180 and 240*240, the power corresponding to the designed reflection phase is very consistent with the optimal received signal power, which shows that the reflection phase designed by the present invention is very effective.

[0128] Figure 5 The figure plots the power loss ratio Γ as a function of the number of subsurfaces. It can be observed that the power loss ratio decreases as the number of subsurfaces increases. This is because the Rayleigh distance decreases with increasing subsurfaces, resulting in a more accurate far-field model. It can be observed that when the smart reflector is of reasonable size, a 240×240 far-field model is sufficient to describe the radiation field characteristics of electromagnetic waves.

Claims

1. A method for establishing a UAV millimeter wave channel model based on modular intelligent reflective surfaces, characterized in that: The following steps are involved: S1. A UAV millimeter wave communication system assisted by an intelligent reflecting surface is established, and a UAV millimeter wave near-field channel model assisted by an intelligent reflecting surface is established, and the complex channel gain of the UAV millimeter wave near-field channel model assisted by an intelligent reflecting surface is obtained; S2. Divide the smart reflective surface into multiple identical submodules and renumber the reflective units within each submodule to establish a UAV millimeter-wave near-field channel model based on the modularization of the smart reflective surface. Obtain the complex channel gain of the UAV millimeter-wave near-field channel model based on the modularization of the smart reflective surface. S3. Simplify the UAV millimeter-wave near-field channel model based on the modularization of the intelligent reflecting surface in step S2, use plane waves instead of spherical waves to simulate the propagation characteristics of electromagnetic waves, establish a UAV millimeter-wave far-field channel model based on the modularization of the intelligent reflecting surface, and obtain the complex channel gain of the far-field channel model; design the reflection phase of the modularized intelligent reflecting surface based on the maximization criterion of the reflection unit gain of the far-field channel model, and the designed reflection phase includes the reflection phase related to the reflection unit and the reflection phase related to the sub-module; the reflection phase related to the reflection unit is determined by the plane wave assumption, and the reflection phase related to the sub-module is determined by the spherical wave assumption; S4. Using the reflection phase of the designed modularized smart reflector, solve the approximate closed-form expression of the received signal power of the UAV millimeter-wave near-field channel model based on the modularized smart reflector; S5. Based on the obtained approximate closed-form expression of the received signal power, the reflection phase after modularization of the designed smart reflector is used to calculate the power loss ratio of the UAV millimeter-wave near-field channel model based on the modularization of the smart reflector. Using the obtained power loss ratio, the impact of the smart reflector block scheme on the performance gain of the UAV millimeter-wave system is explored.

2. The method for establishing a UAV millimeter wave channel model based on intelligent reflective surface modularization according to claim 1 is characterized in that: The complex channel gain h of the UAV millimeter wave near-field channel model based on the intelligent reflector in step S1 is 1,p Expressed as: Where π represents the circumference of a circle, δ1 and δ2 represent the spacing between adjacent row and column reflective units on the smart reflective surface, λ represents the wavelength of the electromagnetic wave emitted by the drone, N1 and N2 are the number of row and column reflective units on the smart reflective surface, and γ a and γ d They represent the path losses from the UAV to the smart reflective surface and from the smart reflective surface to the receiving end, It represents the projection of the electromagnetic wave emitted by the drone on the normal line of the smart reflective surface. represents the projection of the electromagnetic wave signal reflected by the smart reflective surface on the normal line of the smart reflective surface, e represents the exponential function, Indicates the distance from the pth transmitting antenna of the drone to the (n2,n1)th reflecting unit, Indicates the distance from the (n2, n1)th reflector unit to the receiving antenna, Represents the reflection phase of the (n2, n1)th reflection unit on the smart reflection surface.

3. The method for establishing a UAV millimeter wave channel model based on intelligent reflective surface modularization according to claim 1 is characterized in that: The complex channel gain h of the UAV millimeter wave near-field channel model with modular intelligent reflector in step S2 is 2,p Expressed as: Where π represents the circumference of a circle, δ1 and δ2 represent the spacing between adjacent row and column reflection units on the smart reflective surface, λ represents the wavelength of the electromagnetic wave emitted by the drone, and γ a and γ d They represent the path losses from the UAV to the smart reflective surface and from the smart reflective surface to the receiving end, It represents the projection of the electromagnetic wave emitted by the drone on the normal line of the smart reflective surface. represents the projection of the electromagnetic wave signal reflected by the smart reflective surface on the normal line of the smart reflective surface, Q represents the number of submodules of the smart reflective surface, q represents the subscript index of the submodule of the smart reflective surface, M1 and M2 represent the number of row reflective units and column reflective units in each submodule respectively, m1 and m2 represent the subscript index of the row reflective unit and column reflective unit in each submodule, e represents the exponential function, is the reflection phase of the qth submodule, It represents the distance from the pth transmitting antenna of the UAV to the (m2, m1)th reflector unit in the qth submodule. Represents the distance from the receiving antenna to the (m2, m1)th reflector unit in the qth submodule.

4. The method for establishing a UAV millimeter wave channel model based on intelligent reflective surface modularization according to claim 1 is characterized in that: The complex channel gain h of the UAV millimeter wave far-field channel model based on the intelligent reflector modularization established in step S3 is 3,p , expressed as: Where π represents the circumference of a circle, δ1 and δ2 represent the spacing between adjacent row and column reflection units on the smart reflective surface, λ represents the wavelength of the electromagnetic wave emitted by the drone, and γ a and γ d They represent the path losses from the UAV to the smart reflective surface and from the smart reflective surface to the receiving end, It represents the projection of the electromagnetic wave emitted by the drone on the normal line of the smart reflective surface. represents the projection of the electromagnetic wave signal reflected by the smart reflective surface on the normal line of the smart reflective surface, Q represents the number of submodules of the smart reflective surface, q represents the subscript index of the submodule of the smart reflective surface, M1 and M2 represent the number of row reflective units and column reflective units in each submodule respectively, m1 and m2 represent the subscript index of the row reflective unit and column reflective unit in each submodule, e represents the exponential function, is the reflection phase of the qth submodule, and represents the auxiliary variable, p represents the subscript index of the transmitting antenna unit, P represents the number of transmitting antenna units, δ represents the distance between adjacent transmitting antenna units, Ψ a Represents the angle between the line connecting the drone to the center of the intelligent reflective surface and the positive direction of the x-axis, ε a,q represents the distance from the UAV to the center of the qth submodule on the intelligent reflective surface, ε d,q represents the distance from the receiving antenna to the center of the qth submodule on the smart reflector, Φ a,q represents the angle between the line connecting the drone and the center of the qth submodule of the intelligent reflector and the positive direction of the x-axis, Φ d,q Ω represents the angle between the line connecting the receiving antenna to the center of the qth submodule of the smart reflector and the positive direction of the x-axis. a,q Ω represents the angle between the line connecting the drone and the center of the qth submodule on the intelligent reflector and the positive direction of the z-axis, d,q It represents the angle between the line connecting the receiving antenna to the center of the qth submodule of the smart reflector and the positive direction of the z-axis.

5. The method for establishing a UAV millimeter wave channel model based on intelligent reflective surface modularization according to claim 4 is characterized in that: Based on the maximization criterion of the reflection unit gain of the UAV millimeter-wave far-field channel model under the modular solution, the reflection phase of the modularized smart reflector is designed, including: Complex channel gain h of the UAV millimeter wave far-field channel model based on the modularization of the smart reflector 3,p , the reflection unit gain g(Q,M1,M2) of the smart reflector is expressed as: In order to achieve the maximum reflective unit gain of the smart reflector, the modular reflection phase of the smart reflector is expressed as: Among them, α q represents the constant phase associated with submodule q, It represents the expected angle between the line connecting the drone and the center of the qth submodule of the intelligent reflector and the positive direction of the x-axis. It represents the expected angle between the line connecting the receiving antenna to the center of the qth submodule of the smart reflector and the positive direction of the x-axis. represents the expected angle between the line connecting the drone and the center of the qth submodule on the intelligent reflector and the positive direction of the z-axis, represents the expected angle between the line connecting the receiving antenna to the center of the qth submodule of the smart reflector and the positive direction of the z-axis; Substituting the reflection unit gain g(Q,M1,M2), we have: Among them, sin represents the sine function, θ q , △1 and △2 represent auxiliary variables, which are expressed as: According to the reflection unit gain, when △1=0, △2=0 and When , the reflection unit gain g(Q,M1,M2) has a maximum value g(Q,M1,M2)=QM1M2; and α q The following conditions are met: At this time, and α q Substitution The modular reflection phase of the designed smart reflector is expressed as:

6. The method for establishing a UAV millimeter wave channel model based on intelligent reflective surface modularization according to claim 1 is characterized in that: Step S4 includes: S41, using the second-order Taylor approximation, the distance from the transmitter to the (m2, m1)th reflector unit of the qth submodule The distance from the receiving end to the (m2, m1)th reflector unit of the qth submodule It can be expressed approximately as: Among them, ε a,q represents the distance from the UAV to the center of the qth submodule on the intelligent reflective surface, ε d,q represents the distance from the receiving antenna to the center of the qth submodule on the smart reflector, Ψ a represents the angle between the line connecting the UAV to the center of the smart reflective surface and the positive direction of the x-axis, δ represents the spacing between adjacent antenna units at the transmitting end, δ1 and δ2 represent the spacing between adjacent row reflective units and adjacent column reflective units on the smart reflective surface, respectively. and represents an auxiliary variable, p represents the subscript index of the transmitting antenna unit, P represents the number of transmitting antenna units, M1 and M2 represent the number of row reflection units and column reflection units in each submodule respectively, m1 and m2 represent the subscript index of the row reflection unit and column reflection unit in each submodule, Φ a,q represents the angle between the line connecting the drone and the center of the qth submodule of the intelligent reflector and the positive direction of the x-axis, Φ d,q Ω represents the angle between the line connecting the receiving antenna to the center of the qth submodule of the smart reflector and the positive direction of the x-axis. a,q Ω represents the angle between the line connecting the drone and the center of the qth submodule on the intelligent reflector and the positive direction of the z-axis, d,q It represents the angle between the line connecting the receiving antenna to the center of the qth submodule of the smart reflector and the positive direction of the z-axis; S42, the approximate distance and After substituting the reflection phase designed in step S3 into the complex channel gain of the UAV millimeter wave near-field channel model with modular intelligent reflector in step S2, the received signal power is expressed as: Among them, P r is the received signal power, It represents the projection of the electromagnetic wave emitted by the drone on the normal line of the smart reflective surface. represents the projection of the electromagnetic wave signal reflected by the smart reflective surface on the normal line of the smart reflective surface, ε a represents the distance from the drone to the center of the smart reflective surface, ε d represents the distance from the receiving antenna to the center of the smart reflector, Q represents the number of submodules of the smart reflector, q represents the subscript index of the submodule of the smart reflector, f(η1,η2) is an auxiliary variable, is represented as an auxiliary variable, It is represented as an auxiliary variable, λ represents the wavelength of the electromagnetic wave emitted by the UAV; S43, because and The auxiliary variables f(η1,η2) are expressed as: Among them, x and y are integration variables; S44, make f(η1,η2) is further expressed as: Among them, t and τ are integration variables; S45. Using the Fresnel integral function, the received signal power is approximately expressed as: Among them, P t represents the transmitted signal power, C(·) and S(·) are Fresnel functions, and Represented as auxiliary variables.

7. The method for establishing a UAV millimeter wave channel model based on intelligent reflective surface modularization according to claim 1, characterized in that: The power loss ratio Γ of the UAV millimeter wave near-field channel model based on the modular intelligent reflector in step S5 is: Where Q represents the number of submodules of the smart reflective surface, q represents the subscript index of the submodule of the smart reflective surface, C(·) and S(·) represent Fresnel functions, and is represented as auxiliary variables, M1 and M2 represent the number of row reflection units and column reflection units in each submodule respectively, δ1 and δ2 represent the spacing between adjacent row reflection units and adjacent column reflection units on the smart reflection surface respectively, η1 and η2 are represented as auxiliary variables, and λ represents the wavelength of the electromagnetic wave emitted by the UAV.

8. A UAV millimeter wave channel model establishment system based on intelligent reflective surface modularization is characterized by: include: A complex channel gain calculation unit is used for the UAV millimeter wave communication system assisted by the intelligent reflecting surface, establishes a UAV millimeter wave near-field channel model assisted by the intelligent reflecting surface, and obtains the complex channel gain of the UAV millimeter wave near-field channel model assisted by the intelligent reflecting surface; A post-modular complex channel gain calculation unit is used to divide the smart reflective surface into multiple identical sub-modules, renumber the reflective units within each sub-module, establish a UAV millimeter-wave near-field channel model based on the modularization of the smart reflective surface, and obtain the complex channel gain of the UAV millimeter-wave near-field channel model based on the modularization of the smart reflective surface; The reflection phase design unit is used to simplify the UAV millimeter-wave near-field channel model based on the modularization of the intelligent reflector surface. Plane waves are used instead of spherical waves to simulate the propagation characteristics of electromagnetic waves. The millimeter-wave far-field channel model of the UAV based on the modularization of the intelligent reflector surface is established to obtain the complex channel gain of the far-field channel model. The reflection phase of the modularized intelligent reflector surface is designed based on the maximization criterion of the reflector unit gain of the far-field channel model. The designed reflection phase includes the reflection phase related to the reflector unit and the reflection phase related to the submodule. The reflection phase related to the reflector unit is determined by the plane wave assumption, and the reflection phase related to the submodule is determined by the spherical wave assumption. The received signal power approximation unit is used to solve the approximate closed-form expression of the received signal power of the UAV millimeter-wave near-field channel model based on the modularization of the smart reflector by using the reflection phase of the designed smart reflector; The power loss ratio calculation unit is used to calculate the power loss ratio of the UAV millimeter wave near-field channel model based on the modularization of the smart reflector according to the obtained approximate closed-form expression of the received signal power and the reflection phase of the designed smart reflector after modularization; using the obtained power loss ratio, the influence of the smart reflector blocking scheme on the performance gain of the UAV millimeter wave system is explored.

9. An electronic device, characterized in that: The device comprises: a memory storing executable program code; a processor coupled to the memory; The processor calls the executable program code stored in the memory to execute the steps of the method for establishing a UAV millimeter wave channel model based on intelligent reflecting surface modularization according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer instructions, which, when called, are used to execute the steps of the method for establishing a UAV millimeter wave channel model based on intelligent reflective surface modularization according to any one of claims 1 to 7.

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