Method and apparatus for multi-intelligent reflecting surface phase design based on channel model

Abstract

The present disclosure relates to a method and device for designing phase of multiple intelligent reflecting surfaces based on channel model. The method comprises: establishing a channel model of a signal transmitting end and a signal receiving end based on position information of the signal transmitting end, position information of the signal receiving end, position information of the intelligent reflecting surface, position information of the aerial intelligent reflecting surface and position information of at least one scatterer; calculating a first initial phase and a first dynamic phase of the intelligent reflecting surface, a second initial phase and a second dynamic phase of the aerial intelligent reflecting surface based on the channel model, movement information of the aerial intelligent reflecting surface and movement information of the signal receiving end; calculating a first predicted phase of the intelligent reflecting surface and a second predicted phase of the aerial intelligent reflecting surface; and determining the first predicted phase as a first target phase and the second predicted phase as a second target phase under the condition that the accuracy requirement is met. The method can save computing resources, improve computing accuracy and efficiency when designing phase.

Description

Technical Field

[0001] This disclosure relates to the field of communication technology, and in particular to a method and apparatus for multi-intelligent reflector phase design based on a channel model, an electronic device, and a computer-readable storage medium. Background Technology

[0002] Intelligent Reflecting Surfaces (IRS) are composed of subwavelength units (typically between one-tenth and one-half the communication wavelength) and are often used to alter the electromagnetic response of electromagnetic wave signals arriving at their surface, such as amplitude, phase, and frequency characteristics. Through external signal control, real-time signal reconstruction can be achieved. This characteristic enables IRS to modify the communication propagation environment and improve wireless communication quality. As a promising technology in 6G systems, current research on IRS primarily focuses on improving signal quality through phase shifting of the transmitted signal.

[0003] In existing IRS phase design schemes, the IRS surface can be grouped into units according to the phase design requirements in different scenarios, the coverage requirements of the IRS, and the channel model. A phase compensation scheme for each group of surface units can be designed using beamspanning technology. The gain loss caused by beamspanning can be compensated by increasing the number of surface units.

[0004] Alternatively, by jointly optimizing the source node's transmit beamforming, and by placing the aerial intelligent reflector (AIRS, obtained by mounting an IRS in the air) and using three-dimensional passive beamforming to maximize the worst-case signal-to-noise ratio (SNR) for all locations in the target area, as well as reducing the impact of Doppler shift, a three-dimensional (3D) wireless system architecture based on AIRS can be constructed. This architecture features flexible coverage and supports AIRS mobility. However, this scheme does not consider the combination of AIRS and fixed IRS, and its practical implementation requires a significant amount of channel state information, such as the distribution of scatterers in the channel, making it difficult to implement and only supporting narrowband models.

[0005] Another approach is to adjust the phase of the IRS units so that the reflected beams of all units are aligned at the receiver, creating a virtual direct path through the IRS. However, this approach only considers the case where there is one IRS in the channel and does not take into account the possible mobility of the AIRS, which has significant limitations.

[0006] However, existing technologies do not yet have a design for a communication system jointly assisted by IRS and AIRS. They only consider IRS or AIRS. Furthermore, the actual implementation of some phase design schemes requires a large amount of channel state information, making implementation difficult. Summary of the Invention

[0007] In view of this, embodiments of the present disclosure provide a method and apparatus for multi-intelligent reflector phase design based on a channel model, an electronic device, and a computer-readable storage medium to solve the problems existing in the related art.

[0008] A first aspect of this disclosure provides a multi-intelligent reflector phase design method based on a channel model, comprising: establishing a channel model for the signal transmitter and the signal receiver based on the position information of the signal transmitter, the position information of the signal receiver, the position information of the intelligent reflector, the position information of the airborne intelligent reflector, and the position information of at least one scatterer; calculating a first initial phase and a first dynamic phase after a preset time interval for the intelligent reflector based on the channel model and the motion information of the signal receiver; calculating a second initial phase and a second dynamic phase after a preset time interval for the airborne intelligent reflector based on the channel model, the motion information of the airborne intelligent reflector, and the motion information of the signal receiver; using Taylor expansion, calculating a first predicted phase of the intelligent reflector after a preset time interval based on the first initial phase, and calculating a second predicted phase of the airborne intelligent reflector after a preset time interval based on the second initial phase; if the error tolerance of the first predicted phase and the first dynamic phase meets a first preset error tolerance, determining the first predicted phase as the first target phase of the intelligent reflector after a preset time interval; if the error tolerance of the second predicted phase and the second dynamic phase meets a second preset error tolerance, determining the second predicted phase as the second target phase of the airborne intelligent reflector after a preset time interval.

[0009] A second aspect of this disclosure provides a multi-intelligent reflector phase design apparatus based on a channel model, comprising: a modeling module configured to establish a channel model for the signal transmitter and the signal receiver based on position information of a signal transmitter, position information of a signal receiver, position information of an intelligent reflector, position information of an airborne intelligent reflector, and position information of at least one scatterer; and a calculation module configured to calculate a first initial phase and a first dynamic phase after a preset time interval of the intelligent reflector based on the channel model and motion information of the signal receiver; and to calculate the first initial phase of the airborne intelligent reflector and a first dynamic phase after a preset time interval based on the channel model, the motion information of the airborne intelligent reflector, and the motion information of the signal receiver. The calculation module is further configured to use Taylor expansion to calculate the first predicted phase of the intelligent reflector after the preset time interval based on the first initial phase, and to calculate the second predicted phase of the airborne intelligent reflector after the preset time interval based on the second initial phase; the judgment module is configured to determine the first predicted phase as the first target phase of the intelligent reflector after the preset time interval if the error tolerance of the first predicted phase and the first dynamic phase meets the first preset error tolerance; and to determine the second predicted phase as the second target phase of the airborne intelligent reflector after the preset time interval if the error tolerance of the second predicted phase and the second dynamic phase meets the second preset error tolerance.

[0010] A third aspect of this disclosure provides an electronic device, comprising: at least one processor; and a memory for storing at least one processor-executable instruction; wherein the at least one processor is configured to execute the instruction to implement the steps of the above-described channel model-based multi-intelligent reflector phase design method.

[0011] A fourth aspect of this disclosure provides a computer-readable storage medium that, when the instructions in the computer-readable storage medium are executed by a processor of an electronic device, enables the electronic device to perform the steps of the above-described multi-intelligent reflector phase design method based on a channel model.

[0012] The at least one technical solution adopted in the embodiments of this disclosure can achieve the following beneficial effects: by establishing a channel model for the signal transmitter and the signal receiver based on the position information of the signal transmitter, the signal receiver, the intelligent reflector, the airborne intelligent reflector, and the position information of at least one scatterer; calculating the first initial phase and the first dynamic phase after a preset time interval of the intelligent reflector based on the channel model and the motion information of the signal receiver; calculating the second initial phase and the second dynamic phase after a preset time interval of the airborne intelligent reflector based on the channel model, the motion information of the airborne intelligent reflector, and the motion information of the signal receiver; calculating the first predicted phase of the intelligent reflector after a preset time interval based on the first initial phase, and calculating the second predicted phase of the airborne intelligent reflector after a preset time interval based on the second initial phase; if the error tolerance of the first predicted phase and the first dynamic phase meets the first preset error tolerance, determining the first predicted phase as the first target phase of the intelligent reflector after a preset time interval; if the error tolerance of the second predicted phase and the second dynamic phase meets the second preset error tolerance, determining the second predicted phase as the second target phase of the airborne intelligent reflector after a preset time interval, it is possible to avoid repeatedly acquiring channel information when designing the phase, saving computational resources and improving computational efficiency. Attached Figure Description

[0013] To more clearly illustrate the technical solutions in the embodiments of this disclosure, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this disclosure. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0014] Figure 1 A flowchart illustrating a multi-intelligent reflector phase design method based on a channel model provided in this disclosure embodiment;

[0015] Figure 2A This is an application scenario diagram of intelligent reflective surfaces in related technologies;

[0016] Figure 2B This is an application scenario diagram of aerial intelligent reflective surfaces in related technologies;

[0017] Figure 3 This is an application scenario diagram of the channel modeling method proposed in an exemplary embodiment of the present disclosure;

[0018] Figure 4 This is a schematic diagram of a channel model for a signal transmitter and a signal receiver, which is an exemplary embodiment of this disclosure.

[0019] Figure 5A graph illustrating the impact of a phase design method according to an exemplary embodiment of this disclosure on the spatial correlation of a channel;

[0020] Figure 6 A graph illustrating the impact of a phase design method according to an exemplary embodiment of this disclosure on the frequency correlation of a channel;

[0021] Figure 7 A graph illustrating the impact of a phase design method according to an exemplary embodiment of this disclosure on channel capacity;

[0022] Figure 8 This is a schematic diagram of the structure of a uniform linear array antenna at the signal transmitting end of an exemplary embodiment of the present disclosure.

[0023] Figure 9 This is a schematic diagram of the structure of an intelligent reflective surface according to an exemplary embodiment of the present disclosure;

[0024] Figure 10 This is a schematic diagram of the structure of a multi-intelligent reflector phase design device based on a channel model, which is an exemplary embodiment of the present disclosure.

[0025] Figure 11 A schematic diagram of the structure of an electronic device provided in an exemplary embodiment of this disclosure;

[0026] Figure 12 This is a schematic diagram of the structure of a computer system provided for an exemplary embodiment of the present disclosure. Detailed Implementation

[0027] Embodiments of this disclosure will now be described in more detail with reference to the accompanying drawings. While some embodiments of this disclosure are shown in the drawings, it should be understood that this disclosure can be implemented in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided to provide a more thorough and complete understanding of this disclosure. It should be understood that the accompanying drawings and embodiments of this disclosure are for illustrative purposes only and are not intended to limit the scope of protection of this disclosure.

[0028] It should be understood that the steps described in the method embodiments of this disclosure may be performed in different orders and / or in parallel. Furthermore, the method embodiments may include additional steps and / or omit the steps shown. The scope of this disclosure is not limited in this respect.

[0029] The term "comprising" and its variations as used herein are open-ended, meaning "including but not limited to". The term "based on" means "at least partially based on". The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment"; the term "some embodiments" means "at least some embodiments". Definitions of other terms will be given in the description below. It should be noted that the concepts of "first", "second", etc., used in this disclosure are only used to distinguish different devices, modules, or units, and are not intended to limit the order of functions performed by these devices, modules, or units or their interdependencies.

[0030] It should be noted that the terms "a" and "a plurality of" used in this disclosure are illustrative rather than restrictive, and those skilled in the art should understand that, unless otherwise expressly indicated in the context, they should be understood as "one or more".

[0031] The names of messages or information exchanged between multiple devices in the embodiments of this disclosure are for illustrative purposes only and are not intended to limit the scope of such messages or information.

[0032] The following describes in detail, with reference to the accompanying drawings, a method and apparatus for multi-intelligent reflector phase design based on a channel model, an electronic device, and a computer-readable storage medium according to embodiments of the present disclosure.

[0033] Figure 1 This is a flowchart illustrating a multi-intelligent reflector phase design method based on a channel model, provided in an embodiment of this disclosure. Figure 1 As shown, the multi-intelligent reflector phase design method based on the channel model can include:

[0034] S101, Based on the location information of the signal transmitter, the location information of the signal receiver, the location information of the smart reflector, the location information of the airborne smart reflector, and the location information of at least one scatterer, establish a channel model for the signal transmitter and the signal receiver.

[0035] S102, based on the channel model and the motion information of the signal receiver, calculate the first initial phase of the smart reflector and the first dynamic phase after a preset time interval, respectively; based on the channel model, the motion information of the airborne smart reflector and the motion information of the signal receiver, calculate the second initial phase of the airborne smart reflector and the second dynamic phase after a preset time interval, respectively.

[0036] S103, calculate the first predicted phase of the intelligent reflective surface after a preset time interval based on the first initial phase, and calculate the second predicted phase of the airborne intelligent reflective surface after a preset time interval based on the second initial phase.

[0037] S104, if the error tolerance of the first predicted phase and the first dynamic phase meets the first preset error tolerance, the first predicted phase is determined as the first target phase of the intelligent reflector after a preset time interval; if the error tolerance of the second predicted phase and the second dynamic phase meets the second preset error tolerance, the second predicted phase is determined as the second target phase of the intelligent reflector in the air after a preset time interval.

[0038] Specifically, Figure 2A This is an application scenario diagram of intelligent reflective surfaces in related technologies. Figure 2B This diagram illustrates an application scenario of aerial intelligent reflective surfaces in related technologies. In these technologies, intelligent reflective surfaces (IRS, Intelligent Reflecting Surface) 202 can be installed on the exterior surfaces of buildings, billboards, interior ceilings, windows (transmissive intelligent reflective surfaces), vehicle roofs, etc. The following explanation uses the installation of intelligent reflective surfaces on the exterior surfaces of buildings as an example. Figure 2A As shown, this application scenario may include a signal transmitter 201, a smart reflective surface 202, a first signal receiver 203, and a second signal receiver 204. Specifically, when there is no obstruction between the signal transmitter 201 and the first signal receiver 203, the first signal receiver 203 can directly receive the signal transmitted by the signal transmitter 201, or it can receive the signal transmitted by the signal transmitter 201 via the signal reflection path formed by the smart reflective surface 202 laid on the outer surface of the building. When there is an obstruction between the signal transmitter 201 and the second signal receiver 204, the second signal receiver 204 cannot directly receive the signal transmitted by the signal transmitter 201 due to the obstruction, nor can it receive the signal transmitted by the signal transmitter 201 via the signal reflection path formed by the smart reflective surface 202 laid on the outer surface of the building. Here, the signal transmitter 201 may be, for example, a base station, the first signal receiver 203 and the second signal receiver 204 may be, for example, terminal devices, and the obstruction may be, for example, a building.

[0039] At this time, as Figure 2B As shown, the IRS can be mounted in the air using unmanned aerial vehicles (UAVs) or high-altitude platforms (HAPs). Figure 2BTaking a drone as an example, an aerial intelligent reflecting surface (AIRS) 205 is obtained. Then, even if the second user 204 is blocked by a building, the aerial intelligent reflecting surface 205 can be used to create a signal reflection path between the base station 201 and the second user 204, so that the second user 204 can receive signals based on this signal reflection path; at the same time, the aerial intelligent reflecting surface 205 can also be used to create a signal reflection path between the base station 201 and the first user 203, so that the first user 203 can receive signals based on this signal reflection path.

[0040] Therefore, compared with the traditional IRS deployment method, AIRS has the following advantages: high-altitude deployment in cities makes it easier to establish a line-of-sight (LoS) path with users; it can achieve panoramic / full-angle reflection, and can be used to serve more users compared with wall deployment; in some cases, compared with ground IRS, there are fewer reflections, which can improve channel quality.

[0041] Figure 3 This diagram illustrates an application scenario of the channel modeling method proposed in an exemplary embodiment of this disclosure. Figure 3 As shown, there are obstructions between the signal transmitter 301 and the signal receiver 302. When the signal transmitter 301 transmits a signal to the signal receiver 302, the signal may be blocked by buildings or other objects, causing the transmission to be interrupted and unable to reach the signal receiver 302. Alternatively, the signal may reach the signal receiver 302 through one or more signal transmission paths.

[0042] like Figure 3 As shown, the signal propagation path to the signal receiver 302 may include the intelligent reflector path (IRS path), the airborne intelligent reflector path (AIRS path), and the single hop ray (SBR path). The IRS path is the signal emitted from the signal transmitter 301, reflected by the intelligent reflector 303 laid on the exterior of the building, and reaches the signal receiver 302 through the first path. The AIRS path is the signal emitted from the signal transmitter 301, reflected by the airborne intelligent reflector 304 mounted on the UAV, and reaches the signal receiver 302 through the second path. The SBR path is the signal emitted from the signal transmitter 301, reflected once by the scatterer 305 located between the signal transmitter 301 and the signal receiver 302, and reaches the signal receiver 302 through the third path.

[0043] Figure 4 This is a schematic diagram of a channel model for a signal transmitter and a signal receiver, as shown in an exemplary embodiment of this disclosure. Figure 4 As shown, embodiments of this disclosure can obtain the signal transmitting end (T)X Location information of the signal receiver (R) X The location information of the signal transmitter, the signal receiver, the intelligent reflector (IRS), the airborne intelligent reflector (AIRS), and at least one scatterer is used to establish a channel model for the signal transmitter and the signal receiver.

[0044] In some embodiments, the motion information of the signal receiver in this disclosure may include the moving speed of the signal receiver and the horizontal motion angle of the signal receiver, and the motion information of the airborne smart reflector may include the moving speed of the airborne smart reflector, the horizontal motion angle of the airborne smart reflector, and the vertical motion angle of the airborne smart reflector.

[0045] Both the smart reflective surface and the airborne smart reflective surface in the embodiments of this disclosure can include multiple reflective units. The first initial phase can include a corresponding number of first sub-initial phases, the first dynamic phase can include a corresponding number of first sub-dynamic phases, the first predicted phase can include a corresponding number of first sub-predicted phases, and the first target phase can include a corresponding number of first sub-target phases.

[0046] The second initial phase may include a corresponding number of second sub-initial phases, the second dynamic phase may include a corresponding number of second sub-dynamic phases, the second prediction phase may include a corresponding number of second sub-predictive phases, and the second target phase may include a corresponding number of second sub-target phases.

[0047] Specifically, if the total number of reflective units contained in the intelligent reflective surface configured in this embodiment of the present disclosure is N IRS indivual, This indicates the number of reflective units contained in the intelligent reflective surface along the x-axis. This indicates the number of reflective units contained in the intelligent reflective surface along the y-axis.

[0048] If the total number of reflective units contained in the aerial intelligent reflective surface configured in this embodiment of the present disclosure is N AIRS indivual, This indicates the number of reflective units contained in the intelligent reflective surface along the x-axis. This indicates the number of reflective units contained in the intelligent reflective surface along the y-axis.

[0049] In practical applications, taking the intelligent reflective surface diameter as an example, the embodiments of this disclosure can first determine the phase of the signal transmitting end and the signal receiving end after passing through the intelligent reflective surface diameter, and then align them with the center of the intelligent reflective surface as a reference. Based on this phase, the phase of each reflective element of the intelligent reflective surface can be determined. Similarly, the phase of each reflective element of the aerial intelligent reflective surface can be determined.

[0050] Taking the calculation of the first initial phase of the intelligent reflective surface as an example, if the first initial phase of the center of the intelligent reflective surface is... The phase of the signal receiver is φ, where φ∈(0,2π). At this point, the phase difference between the signal receiver and the signal transmitter due to the propagation distance caused by the intelligent reflector diameter can be determined as k0(ε). T,I +ε I,R (t)), where k0 is the wave number. To compensate for the phase difference between the signal receiver and transmitter due to the propagation distance, we can obtain: Due to the randomness of the scattering path phase, any value of φ is equivalent. To simplify the calculation, we take φ = 0 here. Where, ε T,I ε represents the distance from the center of the signal transmitter to the center of the smart reflector. I,R (t) represents the distance from the center of the smart reflector to the center of the signal receiver.

[0051] Based on this, the first sub-initial phase of the nth reflecting unit of the smart reflective surface can be determined as follows: in, This represents the first sub-initial phase of the nth reflecting unit of the smart reflector. This represents the distance from the signal transmitter to the nth reflecting unit of the smart reflector. This represents the distance from the nth reflecting unit of the smart reflector to the signal receiver.

[0052] For example, in embodiments of this disclosure, the first sub-initial phase of the nth reflecting unit of the smart reflective surface can be calculated using the following first formula, second formula, third formula, fourth formula, and fifth formula, wherein the first formula, second formula, third formula, fourth formula, and fifth formula are respectively:

[0053]

[0054]

[0055]

[0056]

[0057] ε I,R (t)=[D+vR tcosχ R -x I ,v R tsinχ R -y I ,-H IRS ] T ,

[0058] in, This represents the first sub-initial phase of the nth reflecting unit of the smart reflector, where n is an integer greater than or equal to 1 and less than or equal to N, N is the total number of reflecting units in the smart reflector, and k0 represents the wave number. t represents time t (i.e., the initial time). This represents the distance vector from the signal transmitter to the nth reflecting unit of the smart reflector. ε represents the distance vector from the nth reflecting unit of the smart reflector to the signal receiver. T,I ε represents the distance vector from the center of the signal transmitter to the center of the smart reflector. I,R (t) represents the distance vector from the center of the intelligent reflector to the center of the signal receiver, x I The x-coordinate of the intelligent reflective surface is represented by the x-coordinate on the x-axis, and the y-coordinate by the y-coordinate. I H represents the y-coordinate of the intelligent reflective surface on the y-axis. IRS H represents the height of the intelligent reflective surface. BS Indicates the height of the signal transmitter. This represents the distance vector from the first antenna element to the p-th antenna element in a uniform linear antenna array at the signal transmitter. This represents the distance vector from the first antenna element to the qth antenna element in a uniform linear antenna array at the signal receiver. Let v represent the distance vector from the center of the intelligent reflective surface to the nth reflecting unit of the intelligent reflective surface, where D is the initial distance between the signal receiver and the signal transmitter. R χ represents the moving speed of the signal receiver. R The x-angle represents the horizontal motion angle of the signal receiver. I y I ε T,I ε I,R (t), H IRS H BS , D、v R and χ R All parameters are known, x I y I ε T,I ε I,R (t), H IRS H BS And D are determined based on the channel model;

[0059] Based on the first, second, third, fourth, and fifth formulas, the first sub-dynamic phase of the nth reflecting unit of the smart reflective surface is calculated using the sixth formula, whereby:

[0060]

[0061] in, This represents the first sub-dynamic phase of the nth reflecting unit of the intelligent reflective surface after a preset time interval, where Δt represents the preset time interval. This represents the distance from the nth reflecting unit of the intelligent reflective surface to the signal receiver after a preset time interval;

[0062] The first sub-predicted phase of the nth reflective unit of the intelligent reflective surface after a preset time interval is calculated using formulas 7 and 8, where formulas 7 and 8 are respectively:

[0063]

[0064]

[0065] in, This represents the first sub-predicted phase of the nth reflecting unit of the intelligent reflective surface after a preset time interval. This indicates the phase that needs to be adjusted for the nth reflecting unit of the intelligent reflective surface after a preset time interval. It is determined based on the Taylor expansion method;

[0066] The embodiments of this disclosure can calculate the second sub-initial phase of the nth reflective unit of the airborne intelligent reflector using the following ninth formula, tenth formula, eleventh formula, twelfth formula, and thirteenth formula, respectively:

[0067]

[0068]

[0069]

[0070]

[0071]

[0072] in, This represents the second sub-initial phase of the nth reflecting unit of the aerial intelligent reflector. This represents the distance vector from the signal transmitter to the nth reflecting unit of the airborne intelligent reflector. ε represents the distance vector from the nth reflecting unit of the airborne intelligent reflector to the signal receiver. T,A (t) represents the distance vector from the center of the signal transmitter to the center of the airborne intelligent reflector, ε A,R (t) represents the distance vector from the center of the airborne intelligent reflector to the center of the signal receiver, x A (t) represents the x-coordinate of the intelligent aerial reflector on the x-axis, y A (t) represents the y-coordinate of the intelligent aerial reflector on the y-axis, z A (t) represents the vertical coordinate of the aerial intelligent reflector on the z-axis, H AIRS Indicates the height of the aerial intelligent reflector. x represents the distance vector from the center of the airborne intelligent reflector to the nth reflecting unit of the airborne intelligent reflector. A (t), y A (t), z A (t), ε T,A (t), ε A,R (t), H AIRS , D、v R and χ R All parameters are known, x A (t), y A (t), z A (t), ε T,A (t), ε A,R (t), H AIRS And D are determined based on the channel model;

[0073] Based on formulas 9, 10, 11, 12, and 13, formula 14 is used to calculate the second sub-dynamic phase of the nth reflective unit of the airborne intelligent reflector after a preset time interval. Formula 14 is as follows:

[0074]

[0075] in, Δt represents the first sub-dynamic phase of the nth reflecting unit of the aerial intelligent reflector after a preset time interval, where Δt represents the preset time interval. This represents the distance from the signal transmitter to the nth reflecting unit of the airborne intelligent reflector after a preset time interval. This represents the distance from the nth reflecting unit of the aerial intelligent reflector to the signal receiver after a preset time interval;

[0076] The second sub-predicted phase of the nth reflective unit of the airborne intelligent reflector after a preset time interval is calculated using formulas fifteen and sixteen, where formulas fifteen and sixteen are respectively:

[0077]

[0078]

[0079] in, This represents the second sub-predicted phase of the nth reflective unit of the aerial intelligent reflector after a preset time interval. This indicates the phase that needs to be adjusted for the nth reflecting unit of the aerial intelligent reflector after a preset time interval. It is determined based on the Taylor expansion method.

[0080] Therefore, at any given time, the first sub-initial phase, the first sub-dynamic phase, the second sub-initial phase, the second sub-dynamic phase, and the second sub-predicted phase are all precise values ​​obtained by the phase calculation method of the present disclosure embodiment; the first sub-predicted phase and the second sub-predicted phase are both estimated values ​​obtained by the Taylor expansion method of the present disclosure embodiment.

[0081] In S102, the first preset error tolerance can be defined as the error tolerance of the first sub-predicted phase and the first sub-dynamic phase of each reflective unit of the intelligent reflective surface being less than or equal to a first preset threshold at any given time. The error tolerance of the first sub-predicted phase and the first sub-dynamic phase can be the ratio of the difference between the first sub-predicted phase and the first sub-dynamic phase to the first sub-dynamic phase. The first preset threshold can be determined according to the actual application scenario and is not specifically limited here. In the method of this embodiment, the first preset threshold can be 10%.

[0082] In S103, the second preset error tolerance can be defined as the error tolerance of the second sub-predicted phase and the second sub-dynamic phase of each reflecting unit of the airborne intelligent reflector being less than or equal to a second preset threshold at any given time. The error tolerance of the second sub-predicted phase and the second sub-dynamic phase can be the ratio of the difference between the second sub-predicted phase and the second sub-dynamic phase to the second sub-dynamic phase. The second preset threshold can be determined according to the actual application scenario and is not specifically limited here. In the method of this embodiment, the second preset threshold can be 10%.

[0083] In practical applications, both the controllers of the smart reflector and the airborne smart reflector need to adjust their respective phases in real time to meet communication quality requirements, which undoubtedly increases the burden on the controllers. Therefore, in the embodiments of this disclosure, if the phases predicted by the Taylor expansion method (the first predicted phase and the second predicted phase) meet the error tolerance requirements, the first predicted phase can be determined as the first sub-target phase of the smart reflector after a preset time interval, and the second predicted phase can be determined as the second sub-target phase of the airborne smart reflector after a preset time interval. This can save resources and improve computational efficiency when designing the phases.

[0084] In some embodiments, this disclosure can utilize channel statistical characteristics to evaluate the channel quality of the signal transmitter and receiver, and to evaluate the aforementioned multi-intelligent reflector phase design method based on a channel model. The channel statistical characteristics of this disclosure can include a space-time autocorrelation function, a frequency autocorrelation function, and channel capacity; all three are related to the channel impulse response of the signal transmitter and receiver. Therefore, the method of this disclosure can further include:

[0085] Based on the channel model, phase information of the smart reflector, phase information of the airborne smart reflector, phase information of at least one scatterer, motion information of the airborne smart reflector, and motion information of the signal receiver, the channel impulse response of the signal transmitter and signal receiver is calculated using the following seventeenth formula. The channel impulse response of the signal transmitter and signal receiver includes the channel impulse response of the smart reflector diameter, the channel impulse response of the airborne smart reflector diameter, and the channel impulse response of a single-hop path; where the seventeenth formula is:

[0086]

[0087] Among them, h pq (t,τ) represents the channel impulse response at the signal transmitter and the signal receiver. The channel impulse response representing the intelligent reflector diameter, The channel impulse response represents the airborne intelligent reflector diameter. Let t represent the channel impulse response of a single hop path, τ represent time, and t represent time delay.

[0088] It should be noted that, here, the phase information of the intelligent reflector is the first target phase of the intelligent reflector in S104, and the phase information of the airborne intelligent reflector is the second target phase of the airborne intelligent reflector in S104.

[0089] For example, the method in this disclosure embodiment may further include: determining the channel impulse response of the smart reflector diameter based on the channel model, the phase information of the smart reflector, and the motion information of the signal receiver, and calculating the channel impulse response of the smart reflector diameter using the following eighteenth formula, wherein the eighteenth formula is:

[0090]

[0091] Among them, K Rice The sum of the Rice factors of the airborne intelligent reflector diameter and the intelligent reflector diameter is used to determine power distribution, K. Rice =K IRS +K AIRS K AIRS The Rice factor, K, represents the diameter of an airborne intelligent reflector.IRS The Rice factor, n, represents the diameter of the intelligent reflective surface. i N represents the nth reflecting unit of the smart reflective surface. IRS The total number of reflective elements for the intelligent reflective surface diameter. Let j represent the first sub-initial phase of the nth reflecting unit of the smart reflector, where j is the imaginary unit and λ represents the wavelength. This represents the distance from the signal transmitter to the nth reflecting unit of the smart reflector. v represents the distance from the nth reflecting unit of the smart reflector to the signal receiver. R The speed of the signal receiver is represented by t, and time is represented by t. Indicates the orientation angle between the signal receiver and the smart reflector. χ represents the elevation angle between the signal receiver and the smart reflector. R τ represents the horizontal motion angle of the signal receiver. IRS (t) represents the time delay of the intelligent reflector after propagation through the channel, and δ(·) represents the impulse function, δ(τ-τ IRS (t) represents the channel impulse response of the smart reflector diameter.

[0092] For example, the method of this disclosure embodiment may further include: calculating the channel impulse response of the airborne smart reflector based on the channel model, the phase information of the airborne smart reflector, the motion information of the airborne smart reflector, and the motion information of the signal receiver, using the following nineteenth formula, wherein the nineteenth formula is:

[0093]

[0094] Among them, K Rice The sum of the Rice factors of the airborne intelligent reflector diameter and the intelligent reflector diameter is used to determine power distribution, K. Rice =K IRS +K AIRS K AIRS The Rice factor, K, represents the diameter of an airborne intelligent reflector. IRS The Rice factor, n, represents the diameter of the intelligent reflective surface. a N represents the nth reflecting unit of the aerial intelligent reflector. AIRS The total number of reflective elements for the intelligent aerial reflector. Let j represent the second sub-initial phase of the nth reflecting unit of the aerial intelligent reflector, where j is the imaginary unit and λ represents the wavelength. This represents the distance from the signal transmitter to the nth reflecting unit of the airborne intelligent reflector. Let t represent the distance from the nth reflecting unit of the airborne intelligent reflector to the signal receiver, and v represent time. Av represents the moving speed of the intelligent reflector in the air. R This indicates the moving speed of the signal receiver. Indicates the azimuth angle between the signal transmitter and the airborne intelligent reflector. This indicates the elevation angle between the signal transmitter and the airborne intelligent reflector. Indicates the azimuth angle between the signal receiver and the airborne intelligent reflector. This indicates the elevation angle between the signal receiver and the airborne intelligent reflector. This indicates the horizontal motion angle of the intelligent aerial reflector. χ represents the vertical motion angle of the aerial intelligent reflector. R τ represents the horizontal motion angle of the signal receiver. AIRS The time delay of the airborne intelligent reflector after propagation through the channel is represented by δ(·), and δ(τ-τ) represents the impulse function. AIRS (t) represents the channel impulse response of the airborne intelligent reflector diameter.

[0095] For example, the method in this disclosure embodiment may further include: calculating the channel impulse response of a single hop path based on a channel model, phase information of at least one scatterer, and motion information of the signal receiver, using the following twentieth formula, wherein the twentieth formula is:

[0096]

[0097] Among them, K Rice The sum of the Rice factors of the airborne intelligent reflector diameter and the intelligent reflector diameter is used to determine power distribution, K. Rice =K IRS +K AIRS K AIRS The Rice factor, K, represents the diameter of an airborne intelligent reflector. IRS The Rice factor represents the diameter of the intelligent reflector surface. There are multiple scatterers, which are divided into clusters, with each cluster containing at least one scatterer. P (c) (t) represents the total power of each cluster of scatterers, C represents the total number of clusters, and M represents the number of scatterers in each cluster. This represents the random phase of the m-th scatterer in the c-th cluster. This represents the distance from the signal transmitter to the m-th scatterer in the c-th cluster. This represents the distance from the m-th scatterer in the c-th cluster to the signal receiver. This represents the directional angle between the signal receiver and the m-th scatterer in the c-th cluster. This represents the elevation angle between the signal receiver and the m-th scatterer in the c-th cluster. The time delay of the c-th cluster scatterer propagating through the channel is represented by δ(·), and δ(·) represents the impulse function. This represents the channel impulse response of a single hop path.

[0098] For example, in this embodiment of the disclosure, the space-time autocorrelation function can be calculated using the twenty-first formula, wherein the twenty-first formula is:

[0099]

[0100] Where, ρ (pq),(p′q′) (t;Δp,Δq,Δt) denotes the space-time autocorrelation function. The expected value operator is represented by *, the conjugate operator is represented by ||·||, the Euclidean norm is represented by Δp and Δq, and h represents the change in antenna spacing. pq (·) represents the channel impulse response, h pq (t) represents the channel impulse response at time t, h p′q′ (t+Δt) represents the channel impulse response after a preset time interval.

[0101] The aforementioned space-time autocorrelation function can include both time autocorrelation function and spatial autocorrelation function. When Δp = Δq = 0, the time autocorrelation function can be calculated separately, and when Δt = 0, the spatial autocorrelation function can be calculated separately.

[0102] Figure 5 A graph illustrating the impact of a phase design method according to an exemplary embodiment of this disclosure on the spatial correlation of a channel. Figure 5 As shown, "no phase adjustment" indicates that the phase design method of this disclosure embodiment is not used, while "phase adjustment" indicates that the phase is adjusted using the phase design method of this disclosure embodiment. A 3×3 element indicates that the airborne intelligent reflector and the intelligent reflector contain 3 elements in both the vertical and horizontal directions, for a total of 9 elements; a 10×10 element indicates that the airborne intelligent reflector and the intelligent reflector contain 3 elements in both the vertical and horizontal directions, for a total of 100 elements. From... Figure 5 It can be seen that the spatial correlation of the channel after phase adjustment is more stable. Therefore, the effectiveness of the phase design method proposed in the embodiments of this disclosure is proven.

[0103] For example, in this embodiment of the disclosure, the frequency autocorrelation function can be calculated using the twenty-second formula, wherein the twenty-second formula is:

[0104]

[0105] Where, ρ pq (t,Δf) represents the frequency autocorrelation function, H pq (·) represents channel state information, H pq (t,f) represents the channel state information at time t with frequency f, H pq(t,f+Δf) represents the channel state information at time t with frequency f+Δf, where f represents the frequency, Δf represents the change in frequency, and H pq (·) is based on h pq (·) is obtained by performing a Fourier transform.

[0106] Figure 6 A graph illustrating the impact of a phase design method according to an exemplary embodiment of this disclosure on the frequency correlation of a channel. Figure 6 As shown, the meanings of no phase adjustment, phase adjustment, 3×3 element, and 10×10 element are explained above and will not be repeated here. From Figure 8 It can be seen that after phase adjustment, the frequency correlation at certain frequencies is significantly reduced, and the low frequency correlation is conducive to frequency diversity. Therefore, the effectiveness of the phase design method proposed in the embodiments of this disclosure is proven.

[0107] For example, in this embodiment of the disclosure, the channel capacity can be calculated using the twenty-third formula, wherein the twenty-third formula is:

[0108]

[0109] Among them, C capacity (t) represents the channel capacity, ρ is the average received signal-to-noise ratio, and L T H is the number of transmitting antennas, and H(t) represents the channel matrix. H H(t) represents the transpose of the channel matrix, det represents the determinant of the matrix, and the size of the channel matrix H(t) is P×Q, where P is the number of antenna elements at the transmitting end and Q is the number of antenna elements at the receiving end. Each element in the channel matrix is ​​the channel impulse response h between the p-th antenna element at the transmitting end and the q-th antenna element at the receiving end. pq (t,τ).

[0110] Figure 7 This is a graph illustrating the impact of a phase design method according to an exemplary embodiment of this disclosure on channel capacity. Figure 7 As shown, "not using the phase adjustment method" indicates that the phase design method of this disclosure embodiment is not used; "using the phase adjustment method entirely" indicates that the phase design method of this disclosure embodiment is used for both the airborne intelligent reflector and the intelligent reflector; "using the phase adjustment method only for the IRS" indicates that the phase design method of this disclosure embodiment is used only for the intelligent reflector; and "using the phase adjustment method only for the AIRS" indicates that the phase design method of this disclosure embodiment is used only for the airborne intelligent reflector. From Figure 7It can be seen that whether phase adjustment is used on all channels, only on the IRS, or only on the AIRS, there is an improvement in channel capacity compared to not using phase adjustment. Therefore, the effectiveness of the phase design method proposed in this disclosure is proven.

[0111] In some embodiments of this disclosure, both the signal transmitter and the signal receiver can be a uniform linear array (ULA) antenna. Figure 8 This is a schematic diagram of the structure of a uniform linear array antenna at the signal transmitting end of an exemplary embodiment of this disclosure. Figure 8 As shown, with the first antenna element as the center, δ represents the distance vector from the first antenna element to the p-th antenna element in a uniform linear antenna array at the signal transmitter. T α represents the spacing between antenna elements at the signal transmitting end. T β represents the azimuth angle of the uniform linear antenna array at the signal transmitting end. T This represents the elevation angle of the uniform linear antenna array at the signal transmitter. Based on this, the distance vector from the 1st antenna element to the pth antenna element in the uniform linear antenna array at the signal transmitter is calculated using the 24th formula, where the 24th formula is:

[0112]

[0113] δ in the twenty-fourth formula T Replace with an antenna element spacing of δ at the signal receiver end R The twenty-fifth formula can be obtained, which is used to calculate the distance vector from the first antenna element to the qth antenna element in a uniform linear antenna array at the signal receiver. The twenty-fifth formula is:

[0114]

[0115] Figure 9 This is a schematic diagram of the structure of an intelligent reflective surface according to an exemplary embodiment of this disclosure. Figure 9 As shown, δ h δ represents the size of the reflective unit of the intelligent reflective surface in the horizontal direction. v φ represents the size of the reflective unit of the intelligent reflective surface in the vertical direction. IRS ψ represents the horizontal rotation angle of the intelligent reflective surface. IRS δ represents the vertical rotation angle of the intelligent reflective surface. h δ represents the size of the reflective unit of the intelligent reflective surface in the horizontal direction. vThis represents the size of the reflective element of the intelligent reflective surface in the vertical direction. Based on this, the distance vector from the center of the intelligent reflective surface to the nth reflective element is calculated using the twenty-sixth formula, where the twenty-sixth formula is:

[0116]

[0117] Here, (h,v) represents the nth reflecting unit, h = 1, 2, 3…H, v = 1, 2, 3…V, H represents the total number of reflecting units in the horizontal direction, and V represents the total number of reflecting units in the vertical direction.

[0118] In the twenty-sixth formula, φ IRS Replace with the horizontal rotation angle φ of the aerial intelligent reflector. AIRS , ψ IRS Replace with the vertical rotation angle ψ of the aerial intelligent reflector. AIRS The twenty-seventh formula can be obtained, and the distance vector from the center of the airborne intelligent reflector to the nth reflecting unit of the airborne intelligent reflector can be calculated using the twenty-seventh formula:

[0119]

[0120] In some embodiments, the present disclosure embodiments can use formulas 28, 29, and 30 to calculate the time delay of the intelligent reflector diameter after propagation through the channel, the time delay of the airborne intelligent reflector diameter after propagation through the channel, and the time delay of the single-hop path propagating through the channel to the c-th cluster scatterer, respectively. Formulas 28, 29, and 30 are as follows:

[0121] τ IRS (t)=(ε T,I +ε I,R (t)) / c light ,

[0122] τ AIRS (t)=(ε T,A (t)+ε A,R (t)) / c light ,

[0123]

[0124] Among them, c light This represents the speed of light in a vacuum. The meanings of the other parameters are explained in the previous text and will not be repeated here.

[0125] In some embodiments, the present disclosure embodiments can calculate the abscissa of the airborne intelligent reflector on the x-axis, the ordinate of the airborne intelligent reflector on the y-axis, and the ordinate of the airborne intelligent reflector on the z-axis using formulas 31, 32, and 33, respectively. Formulas 31, 32, and 33 are as follows:

[0126]

[0127]

[0128]

[0129] Where, x A (0) represents the x-coordinate of the intelligent reflective surface in the air at the initial moment, and y A (0) represents the y-coordinate of the intelligent reflective surface in the air at the initial moment. The meanings of other parameters are explained in the previous text and will not be repeated here.

[0130] In some embodiments, the present disclosure can use formulas thirty-four and thirty-five to calculate the azimuth angle and elevation angle between the signal receiver and the smart reflector, respectively.

[0131]

[0132]

[0133] The specific meanings of the parameters are explained in the previous text and will not be repeated here.

[0134] In some embodiments, the present disclosure embodiments can use formulas 36, 37, 38, and 39 to calculate the azimuth angle between the signal transmitter and the airborne intelligent reflector, the elevation angle between the signal transmitter and the airborne intelligent reflector, the azimuth angle between the signal receiver and the airborne intelligent reflector, and the elevation angle between the signal receiver and the airborne intelligent reflector, respectively.

[0135]

[0136]

[0137]

[0138]

[0139] The specific meanings of the parameters are explained in the previous text and will not be repeated here.

[0140] In some embodiments, the present disclosure embodiments can use formulas 40, 41, 42, and 43 to calculate the distance vector from the m-th scatterer of the c-th cluster to the signal receiver, the distance vector from the signal transmitter to the m-th scatterer of the c-th cluster, the orientation angle between the signal receiver and the m-th scatterer of the c-th cluster, and the elevation angle between the signal receiver and the m-th scatterer of the c-th cluster, respectively. Formulas 40, 41, 42, and 43 are as follows:

[0141]

[0142]

[0143]

[0144]

[0145] in, Let m represent the distance between the m-th scatterer of the c-th cluster at the initial moment and the signal receiver; this is a known quantity. This represents the directional angle between the m-th scatterer of the c-th cluster and the signal receiver at the initial moment. This represents the elevation angle between the m-th scatterer of the c-th cluster and the signal receiver at the initial moment. The meanings of other parameters are explained above and will not be repeated here.

[0146] In practical applications, scatterers are randomly distributed in clusters, and the angular distribution of each cluster follows a truncated Gaussian distribution. Therefore, in the method of this disclosure embodiment, and It is calculated randomly, let's assume or θ is randomly calculated using the forty-fourth formula, which is:

[0147]

[0148] f(θ,μ θ ,σ θ ,θ low ,θ up φ(·) represents the probability density function of the truncated Gaussian distribution, φ(·) represents the probability density function of the standard normal distribution, Φ(·) represents the distribution function of the standard normal distribution, and μ θ σ represents the mean of the angular distribution to be calculated. θ θ represents the variance of the angular distribution to be calculated. low θ represents the lower limit of the cutoff angle. up This indicates the upper limit of the cutoff angle, where θ is the angle to be calculated.

[0149] In some embodiments, according to the 3GPPTR 38.901 protocol, in the Umi scenario, the total power of each cluster of scatterers can be calculated using formula forty-fifth, wherein formula forty-fifth is:

[0150]

[0151] Where, r τ It is the time delay scaling function (scene-dependent), DS is the time delay spread, and Z is the time delay scaling function. c It is a random variable that follows a Gaussian distribution. The meanings of the other parameters are explained in the previous text and will not be repeated here.

[0152] In some embodiments, this disclosure can be applied to (1+x). 1 / 2 Performing a Taylor expansion at x = 0 yields the forty-sixth formula, which is:

[0153]

[0154] in, Represents x 2 And higher-order infinitesimals of higher powers, that is, (1+x) under the condition of acceptable precision. 1 / 2 It can be approximated as

[0155] Taking the IRS path as an example, if we use formulas 47 and 48 to calculate the distance from the nth reflecting unit of the smart reflector to the signal receiver, and the predicted distance from the nth reflecting unit of the smart reflector to the signal receiver after a preset time interval, then...

[0156]

[0157] in, This represents the predicted distance from the nth reflecting unit of the intelligent reflective surface to the signal receiver after a preset time interval. The meanings of other parameters are explained above and will not be repeated here.

[0158] For ease of calculation, let X = Dx I +v R tcosχ R Y = v R tsinχ R -y I Then it can be calculated using the forty-ninth formula. The forty-ninth formula is:

[0159]

[0160] The specific meanings of the parameters are explained in the previous text and will not be repeated here.

[0161] At this point, the phase that needs to be adjusted for the nth reflecting unit of the intelligent reflective surface after the preset time interval can be calculated using formulas 49 and 50. Formula 50 is as follows:

[0162]

[0163] The specific meanings of the parameters are explained in the previous text and will not be repeated here.

[0164] Based on this, the embodiments of this disclosure can calculate the phase change of the smart reflector in time t+Δt using the 50th formula within time Δt, while keeping the moving direction of the signal receiver unchanged. This eliminates the need to repeatedly acquire channel information, saves computing resources, and improves computing efficiency.

[0165] The at least one technical solution adopted in the embodiments of this disclosure can achieve the following beneficial effects: by establishing a channel model for the signal transmitter and the signal receiver based on the position information of the signal transmitter, the signal receiver, the intelligent reflector, the airborne intelligent reflector, and the position information of at least one scatterer; calculating the first initial phase and the first dynamic phase after a preset time interval of the intelligent reflector based on the channel model and the motion information of the signal receiver; calculating the second initial phase and the second dynamic phase after a preset time interval of the airborne intelligent reflector based on the channel model, the motion information of the airborne intelligent reflector, and the motion information of the signal receiver; calculating the first predicted phase of the intelligent reflector after a preset time interval based on the first initial phase, and calculating the second predicted phase of the airborne intelligent reflector after a preset time interval based on the second initial phase; if the error tolerance of the first predicted phase and the first dynamic phase meets the first preset error tolerance, determining the first predicted phase as the first target phase of the intelligent reflector after a preset time interval; if the error tolerance of the second predicted phase and the second dynamic phase meets the second preset error tolerance, determining the second predicted phase as the second target phase of the airborne intelligent reflector after a preset time interval, it is possible to avoid repeatedly acquiring channel information when designing the phase, saving computational resources and improving computational efficiency.

[0166] The foregoing mainly describes the solutions provided by the embodiments of this disclosure. It is understood that, in order to achieve the above functions, the electronic device includes hardware structures and / or software modules corresponding to the execution of each function. Those skilled in the art should readily recognize that, based on the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein, this disclosure can be implemented in hardware or a combination of hardware and computer software. Whether a function is executed in hardware or by computer software driving hardware depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this disclosure.

[0167] This disclosure embodiment can divide the electronic device into functional units according to the above method example. For example, each function can be divided into a separate functional module, or two or more functions can be integrated into one processing module. The integrated module can be implemented in hardware or as a software functional module. It should be noted that the module division in this disclosure embodiment is illustrative and only represents one logical functional division; other division methods may be used in actual implementation.

[0168] By dividing each functional module according to its corresponding function, an exemplary embodiment of this disclosure provides a multi-intelligent reflector phase design device based on a channel model. This multi-intelligent reflector phase design device based on a channel model can be an electronic device or a chip applied to an electronic device. Figure 10 This is a schematic diagram of a multi-intelligent reflector phase design device based on a channel model, as an exemplary embodiment of this disclosure. Figure 10 As shown, the device 1000 includes:

[0169] The module 1001 is configured to establish a channel model for the signal transmitter and the signal receiver based on the location information of the signal transmitter, the location information of the signal receiver, the location information of the smart reflector, the location information of the airborne smart reflector, and the location information of at least one scatterer.

[0170] The calculation module 1002 is configured to calculate, based on the channel model and the motion information of the signal receiver, the first initial phase and the first dynamic phase after a preset time interval of the smart reflector, respectively; and to calculate, based on the channel model, the motion information of the airborne smart reflector and the motion information of the signal receiver, the second initial phase and the second dynamic phase after the preset time interval of the airborne smart reflector, respectively.

[0171] The calculation module 1002 is further configured to calculate the first predicted phase of the smart reflector after the preset time interval based on the first initial phase, and to calculate the second predicted phase of the airborne smart reflector after the preset time interval based on the second initial phase.

[0172] The judgment module 1003 is configured to determine the first predicted phase as the first target phase of the intelligent reflector after the preset time interval if the error tolerance of the first predicted phase and the first dynamic phase meets the first preset error tolerance; and to determine the second predicted phase as the second target phase of the airborne intelligent reflector after the preset time interval if the error tolerance of the second predicted phase and the second dynamic phase meets the second preset error tolerance.

[0173] In some embodiments, the motion information of the signal receiver includes the moving speed of the signal receiver and the horizontal motion angle of the signal receiver; the motion information of the aerial smart reflector includes the moving speed of the aerial smart reflector, the horizontal motion angle of the aerial smart reflector, and the vertical motion angle of the aerial smart reflector; and / or,

[0174] Both the intelligent reflective surface and the aerial intelligent reflective surface include multiple reflective units. The first initial phase includes a corresponding number of first sub-initial phases, the first dynamic phase includes a corresponding number of first sub-dynamic phases, the first predicted phase includes a corresponding number of first sub-predicted phases, and the first target phase includes a corresponding number of first sub-target phases. The second initial phase includes a corresponding number of second sub-initial phases, the second dynamic phase includes a corresponding number of second sub-dynamic phases, the second predicted phase includes a corresponding number of second sub-predicted phases, and the second target phase includes a corresponding number of second sub-target phases.

[0175] In some embodiments, the first sub-initial phase of the nth reflecting unit of the smart reflective surface is calculated using the following first formula, second formula, third formula, fourth formula, and fifth formula, wherein the first formula, second formula, third formula, fourth formula, and fifth formula are respectively:

[0176]

[0177]

[0178]

[0179]

[0180]

[0181] in, This represents the first sub-initial phase of the nth reflecting unit of the smart reflector, where n is an integer greater than or equal to 1 and less than or equal to N, N is the total number of reflecting units of the smart reflector, and k0 represents the wave number. t represents time t (i.e., the initial time). This represents the distance vector from the signal transmitter to the nth reflecting unit of the smart reflector. ε represents the distance vector from the nth reflecting unit of the smart reflective surface to the signal receiving end. T,I ε represents the distance vector from the center of the signal transmitting end to the center of the smart reflective surface. I,R (t) represents the distance vector from the center of the intelligent reflective surface to the center of the signal receiver, xI The x-coordinate of the intelligent reflective surface is represented by the x-coordinate on the x-axis, and the y-coordinate by the y-coordinate. I H represents the y-coordinate of the intelligent reflective surface on the y-axis. IRS H represents the height of the intelligent reflective surface. BS This indicates the height of the signal transmitting end. This represents the distance vector from the first antenna element to the p-th antenna element in the uniform linear antenna array of the signal transmitter. This represents the distance vector from the first antenna element to the qth antenna element in the uniform linear antenna array of the signal receiver. Let D represent the distance vector from the center of the intelligent reflective surface to the nth reflective unit of the intelligent reflective surface, and let D be the initial distance vector between the signal receiver and the signal transmitter. R χ represents the moving speed of the signal receiver. R The x represents the horizontal motion angle of the signal receiving end. I y I ε T,I ε I,R (t), H IRS H BS , D、v R and χ R All parameters are known, x I y I ε T,I ε I,R (t), H IRS H BS And D are determined based on the channel model;

[0182] Based on the first formula, the second formula, the third formula, the fourth formula, and the fifth formula, the first sub-dynamic phase of the nth reflecting unit of the smart reflective surface is calculated using the sixth formula, wherein the sixth formula is:

[0183]

[0184] in, This represents the first sub-dynamic phase of the nth reflecting unit of the intelligent reflective surface after a preset time interval, where Δt represents the preset time interval. This represents the distance from the nth reflecting unit of the intelligent reflective surface to the signal receiving end after a preset time interval;

[0185] The first sub-predicted phase of the nth reflective unit of the smart reflective surface after a preset time interval is calculated using the seventh formula and the eighth formula, wherein the seventh formula and the eighth formula are respectively:

[0186]

[0187]

[0188] in, This represents the first sub-predicted phase of the nth reflective unit of the smart reflective surface after a preset time interval. This indicates the phase that needs to be adjusted for the nth reflecting unit of the smart reflective surface after a preset time interval. It is determined based on the Taylor expansion method;

[0189] The second sub-initial phase of the nth reflective unit of the airborne intelligent reflective surface is calculated using the following formulas: the ninth formula, the tenth formula, the eleventh formula, the twelfth formula, and the thirteenth formula, respectively:

[0190]

[0191]

[0192]

[0193]

[0194]

[0195] in, This represents the second sub-initial phase of the nth reflecting unit of the aerial intelligent reflector. This represents the distance vector from the signal transmitter to the nth reflecting unit of the airborne intelligent reflector. ε represents the distance vector from the nth reflecting unit of the aerial intelligent reflector to the signal receiver. T,A (t) represents the distance vector from the center of the signal transmitter to the center of the airborne intelligent reflector, ε A,R (t) represents the distance vector from the center of the airborne intelligent reflector to the center of the signal receiver, x A (t) represents the x-coordinate of the intelligent aerial reflector on the x-axis, y A (t) represents the ordinate of the aerial intelligent reflective surface on the y-axis, z A (t) represents the vertical coordinate of the aerial intelligent reflective surface on the z-axis, H AIRS This indicates the height of the aforementioned aerial intelligent reflective surface. Let x represent the distance vector from the center of the airborne intelligent reflector to the nth reflecting unit of the airborne intelligent reflector. A (t), yA (t), z A (t), ε T,A (t), ε A,R (t), H AIRS , D、v R and χ R All parameters are known, x A (t), y A (t), z A (t), ε T,A (t), ε A,R (t), H AIRS And D are determined based on the channel model;

[0196] Based on the ninth, tenth, eleventh, twelfth, and thirteenth formulas, the second sub-dynamic phase of the nth reflective unit of the aerial intelligent reflective surface after a preset time interval is calculated using the fourteenth formula, wherein the fourteenth formula is:

[0197]

[0198] in, This represents the first sub-dynamic phase of the nth reflective unit of the aerial intelligent reflective surface after a preset time interval, where Δt represents the preset time interval. This represents the distance from the signal transmitter to the nth reflecting unit of the airborne intelligent reflector after a preset time interval. This represents the distance from the nth reflecting unit of the intelligent aerial reflector to the signal receiver after a preset time interval;

[0199] The second sub-predicted phase of the nth reflective unit of the aerial intelligent reflective surface is calculated using formulas fifteen and sixteen after a preset time interval, wherein formulas fifteen and sixteen are respectively:

[0200]

[0201]

[0202] in, This represents the second sub-predicted phase of the nth reflective unit of the aerial intelligent reflective surface after a preset time interval. This indicates the phase that needs to be adjusted for the nth reflecting unit of the aerial intelligent reflector after a preset time interval. It is determined based on the Taylor expansion method.

[0203] In some embodiments, the calculation module 1002 is configured to calculate the channel impulse response of the signal transmitter and the signal receiver based on the channel model, the phase information of the smart reflector, the phase information of the airborne smart reflector, the phase information of at least one of the scatterers, and the motion information of the airborne smart reflector and the motion information of the signal receiver, using the following seventeenth formula. The channel impulse response of the signal transmitter and the signal receiver includes the channel impulse response of the smart reflector diameter, the channel impulse response of the airborne smart reflector diameter, and the channel impulse response of a single-hop path; wherein the seventeenth formula is:

[0204]

[0205] Among them, h pq (t,τ) represents the channel impulse response of the signal transmitter and the signal receiver. This represents the channel impulse response of the intelligent reflector diameter. This represents the channel impulse response of the aforementioned airborne intelligent reflector diameter. The channel impulse response of the single-hop path is represented by t, where t represents time and τ represents time delay.

[0206] In some embodiments, the calculation module 1002 is configured to determine, based on the channel model, the phase information of the smart reflector, and the motion information of the signal receiver, the channel impulse response of the smart reflector diameter is calculated using the following eighteenth formula:

[0207]

[0208] Among them, K Rice The sum of the Rice factors of the airborne intelligent reflector diameter and the intelligent reflector diameter is used to determine power distribution, K. Rice =K IRS +K AIRS K AIRS K represents the Rice factor of the aerial intelligent reflector diameter. IRS The Rice factor, n, represents the diameter of the intelligent reflective surface. i N represents the nth reflecting unit of the intelligent reflecting surface. IRS The total number of reflective units of the intelligent reflective surface diameter. This represents the first sub-initial phase of the nth reflecting unit of the intelligent reflective surface, where j is the imaginary unit and λ represents the wavelength. This represents the distance from the signal transmitter to the nth reflecting unit of the smart reflective surface. v represents the distance from the nth reflecting unit of the intelligent reflective surface to the signal receiving end. RThe speed of the signal receiver is represented by t, where t represents time. This indicates the orientation angle between the signal receiver and the smart reflector. χ represents the elevation angle between the signal receiver and the smart reflector. R τ represents the horizontal motion angle of the signal receiving end. IRS (t) represents the time delay of the intelligent reflective surface after propagation through the channel, and δ(·) represents the impulse function, δ(τ-τ IRS (t) represents the channel impulse response of the intelligent reflective surface diameter.

[0209] In some embodiments, the calculation module 1002 is configured to calculate the channel impulse response of the airborne smart reflector based on the channel model, the phase information of the airborne smart reflector, the motion information of the airborne smart reflector, and the motion information of the signal receiver, using the following nineteenth formula, wherein the nineteenth formula is:

[0210]

[0211] Among them, K Rice The sum of the Rice factors of the airborne intelligent reflector diameter and the intelligent reflector diameter is used to determine power distribution, K. Rice =K IRS +K AIRS K AIRS K represents the Rice factor of the aerial intelligent reflector diameter. IRS The Rice factor, n, represents the diameter of the intelligent reflective surface. a N represents the nth reflecting unit of the aerial intelligent reflective surface. AIRS The total number of reflective units of the aforementioned intelligent aerial reflective surface diameter. This represents the second sub-initial phase of the nth reflecting unit of the aerial intelligent reflector, where j is the imaginary unit and λ represents the wavelength. This represents the distance from the signal transmitter to the nth reflecting unit of the airborne intelligent reflector. The distance from the nth reflecting unit of the aerial intelligent reflector to the signal receiver is represented by t, where t represents time, and v is the distance from the nth reflecting unit of the aerial intelligent reflector to the signal receiver. A v represents the moving speed of the aerial intelligent reflector. R This indicates the moving speed of the signal receiver. This indicates the azimuth angle between the signal transmitter and the airborne intelligent reflector. This indicates the elevation angle between the signal transmitter and the airborne intelligent reflector. This indicates the azimuth angle between the signal receiver and the aerial intelligent reflector. This indicates the elevation angle between the signal receiver and the aerial smart reflector. This indicates the horizontal motion angle of the aforementioned aerial intelligent reflector. χ represents the vertical motion angle of the aforementioned aerial intelligent reflector. R τ represents the horizontal motion angle of the signal receiving end. AIRS The time delay of the airborne intelligent reflector after propagation through the channel is represented by δ(·), and δ(τ-τ) represents the impulse function. AIRS (t) represents the channel impulse response of the airborne intelligent reflector.

[0212] In some embodiments, the calculation module 1002 is configured to calculate the channel impulse response of the single-hop path based on the channel model, the phase information of at least one of the scatterers, and the motion information of the signal receiver, using the following twentieth formula:

[0213]

[0214] Among them, K Rice The sum of the Rice factors of the airborne intelligent reflector diameter and the intelligent reflector diameter is used to determine power distribution, K. Rice =K IRS +K AIRS K AIRS K represents the Rice factor of the aerial intelligent reflector diameter. IRS The Rice factor representing the diameter of the intelligent reflective surface, wherein there are multiple scatterers, which are divided into clusters, and each cluster includes at least one scatterer, P (c) (t) represents the total power of each cluster of scatterers, C represents the total number of clusters, and M represents the number of scatterers in each cluster. This represents the random phase of the m-th scatterer in the c-th cluster. This represents the distance from the signal transmitter to the m-th scatterer in the c-th cluster. This represents the distance from the m-th scatterer in the c-th cluster to the signal receiver. This represents the directional angle between the signal receiver and the m-th scatterer in the c-th cluster. This represents the elevation angle between the signal receiver and the m-th scatterer of the c-th cluster. The time delay of the c-th cluster scatterer propagating through the channel is represented by δ(·), and δ(·) represents the impulse function. This represents the channel impulse response of a single hop path.

[0215] This disclosure also provides an electronic device, including: at least one processor; a memory for storing at least one processor-executable instruction; wherein the at least one processor is used to execute the instruction to implement the steps of the method disclosed in this disclosure.

[0216] Figure 11 This is a schematic diagram of the structure of an electronic device provided as an exemplary embodiment of this disclosure. For example... Figure 11 As shown, the electronic device 1100 includes at least one processor 1101 and a memory 1102 coupled to the processor 1101. The processor 1101 can perform the corresponding steps in the methods disclosed in the embodiments of this disclosure.

[0217] The processor 1101 described above can also be referred to as a Central Processing Unit (CPU), which can be an integrated circuit chip with signal processing capabilities. Each step in the method disclosed in this embodiment can be implemented by the integrated logic circuitry in the hardware of the processor 1101 or by instructions in software form. The processor 1101 can be a general-purpose processor, a digital signal processor (DSP), an ASIC, a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in this embodiment can be directly implemented by a hardware decoding processor, or by a combination of hardware and software modules in the decoding processor. The software modules can be located in the memory 1102, such as random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, or other mature storage media in the art. The processor 1101 reads information from the memory 1102 and, in conjunction with its hardware, completes the steps of the method described above.

[0218] Furthermore, various operations / processes according to this disclosure, implemented via software and / or firmware, can be transmitted from a storage medium or network to a computer system with a dedicated hardware architecture, for example, Figure 12 The computer system 1200 shown is equipped with the programs that constitute the software. When various programs are installed, the computer system is able to perform various functions, including functions such as those described above. Figure 12 This is a schematic diagram of the structure of a computer system provided for an exemplary embodiment of the present disclosure.

[0219] Computer system 1200 is intended to represent various forms of digital electronic computer devices, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. Electronic devices may also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the present disclosure described and / or claimed herein.

[0220] like Figure 12 As shown, the computer system 1200 includes a computing unit 1201, which can perform various appropriate actions and processes according to a computer program stored in a read-only memory (ROM) 1202 or a computer program loaded from a storage unit 1208 into a random access memory (RAM) 1203. The RAM 1203 may also store various programs and data required for the operation of the computer system 1200. The computing unit 1201, ROM 1202, and RAM 1203 are interconnected via a bus 1204. An input / output (I / O) interface 1205 is also connected to the bus 1204.

[0221] Multiple components in the computer system 1200 are connected to the I / O interface 1205, including: an input unit 1206, an output unit 1207, a storage unit 1208, and a communication unit 1209. The input unit 1206 can be any type of device capable of inputting information into the computer system 1200. The input unit 1206 can receive input numerical or character information and generate key signal inputs related to user settings and / or function control of the electronic device. The output unit 1207 can be any type of device capable of presenting information and may include, but is not limited to, a monitor, speaker, video / audio output terminal, vibrator, and / or printer. The storage unit 1208 may include, but is not limited to, a hard disk and an optical disk. The communication unit 1209 allows the computer system 1200 to exchange information / data with other devices via a network such as the Internet, and may include, but is not limited to, a modem, network card, infrared communication device, wireless communication transceiver, and / or chipset, such as Bluetooth™ device, WiFi device, WiMax device, cellular communication device, and / or the like.

[0222] The computing unit 1201 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the computing unit 1201 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. The computing unit 1201 performs the various methods and processes described above. For example, in some embodiments, the methods disclosed in this disclosure can be implemented as a computer software program tangibly contained in a machine-readable medium, such as storage unit 1208. In some embodiments, part or all of the computer program can be loaded and / or installed on the electronic device 1200 via ROM 1202 and / or communication unit 1209. In some embodiments, the computing unit 1201 can be configured to perform the methods disclosed in this disclosure by any other suitable means (e.g., by means of firmware).

[0223] This disclosure also provides a computer-readable storage medium, wherein when the instructions in the computer-readable storage medium are executed by a processor of an electronic device, the electronic device is able to perform the methods disclosed in this disclosure.

[0224] The computer-readable storage medium in this disclosure can be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. The aforementioned computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specifically, the aforementioned computer-readable storage medium may include electrical connections based on one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0225] The aforementioned computer-readable medium may be included in the aforementioned electronic device; or it may exist independently and not assembled into the electronic device.

[0226] This disclosure also provides a computer program product, including a computer program, wherein when the computer program is executed by a processor, it implements the methods disclosed in the embodiments of this disclosure.

[0227] In embodiments of this disclosure, computer program code for performing the operations of this disclosure can be written in one or more programming languages ​​or a combination thereof. These programming languages ​​include, but are not limited to, object-oriented programming languages ​​such as Java, Smalltalk, and C++, as well as conventional procedural programming languages ​​such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network (including a local area network (LAN) or a wide area network (WAN)), or it can be connected to an external computer.

[0228] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0229] The modules, components, or units described in the embodiments of this disclosure can be implemented in software or hardware. The names of the modules, components, or units do not necessarily constitute a limitation on the module, component, or unit itself.

[0230] The functions described above in this document can be performed at least in part by one or more hardware logic components. For example, without limitation, exemplary hardware logic components that can be used include: field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), system-on-a-chip (SoCs), complex programmable logic devices (CPLDs), and so on.

[0231] The above description is merely an embodiment of this disclosure and an explanation of the technical principles employed. Those skilled in the art should understand that the scope of this disclosure is not limited to technical solutions formed by specific combinations of the above-described technical features, but should also cover other technical solutions formed by arbitrary combinations of the above-described technical features or their equivalents without departing from the above-described concept. For example, technical solutions formed by substituting the above features with (but not limited to) technical features disclosed in this disclosure that have similar functions.

[0232] While specific embodiments of this disclosure have been described in detail by way of example, those skilled in the art should understand that the examples are for illustrative purposes only and not intended to limit the scope of this disclosure. Those skilled in the art should understand that modifications can be made to the above embodiments without departing from the scope and spirit of this disclosure. The scope of this disclosure is defined by the appended claims.

Claims

1. A multi-intelligent reflector phase design method based on a channel model, characterized in that, include: Based on the location information of the signal transmitter, the location information of the signal receiver, the location information of the smart reflector, the location information of the airborne smart reflector, and the location information of at least one scatterer, a channel model for the signal transmitter and the signal receiver is established. Based on the channel model and the motion information of the signal receiver, the first initial phase of the smart reflector and the first dynamic phase of the smart reflector after a preset time interval are calculated respectively. Based on the channel model, the motion information of the airborne intelligent reflector and the motion information of the signal receiver, the second initial phase of the airborne intelligent reflector and the second dynamic phase of the airborne intelligent reflector after the preset time interval are calculated respectively. The first predicted phase of the intelligent reflective surface is calculated based on the first initial phase after the preset time interval, and the second predicted phase of the airborne intelligent reflective surface is calculated based on the second initial phase after the preset time interval. If the error tolerance of the first predicted phase and the first dynamic phase meets the first preset error tolerance, the first predicted phase is determined to be the first target phase of the intelligent reflector after the preset time interval; if the error tolerance of the second predicted phase and the second dynamic phase meets the second preset error tolerance, the second predicted phase is determined to be the second target phase of the airborne intelligent reflector after the preset time interval.

2. The method according to claim 1, characterized in that, The motion information of the signal receiver includes the moving speed of the signal receiver and the horizontal motion angle of the signal receiver; the motion information of the aerial smart reflector includes the moving speed of the aerial smart reflector, the horizontal motion angle of the aerial smart reflector, and the vertical motion angle of the aerial smart reflector; and / or, Both the intelligent reflective surface and the aerial intelligent reflective surface include multiple reflective units. The first initial phase includes the first sub-initial phase of the corresponding reflective units, the first dynamic phase includes the first sub-dynamic phase of the corresponding reflective units, the first predicted phase includes the first sub-predicted phase of the corresponding reflective units, and the first target phase includes the first sub-target phase of the corresponding reflective units. The second initial phase includes the second sub-initial phase of the corresponding reflective units, the second dynamic phase includes the second sub-dynamic phase of the corresponding reflective units, the second predicted phase includes the second sub-predicted phase of the corresponding reflective units, and the second target phase includes the second sub-target phase of the corresponding reflective units.

3. The method according to claim 2, characterized in that, The first sub-initial phase of the nth reflective unit of the smart reflective surface is calculated using the following first formula, second formula, third formula, fourth formula, and fifth formula, wherein the first formula, second formula, third formula, fourth formula, and fifth formula are respectively: ε T,I =[x I ,y I ,H IRS -H BS ] T , ε I,R (t)=[D+v R tcosχ R -x I ,v R sinχ R -the I ,-H IRS ] T , in, This represents the first sub-initial phase of the nth reflecting unit of the smart reflector, where n is an integer greater than or equal to 1 and less than or equal to N, N is the total number of reflecting units of the smart reflector, and k0 represents the wave number. t represents time t (i.e., the initial time). This represents the distance vector from the signal transmitter to the nth reflecting unit of the smart reflector. ε represents the distance vector from the nth reflecting unit of the smart reflective surface to the signal receiving end. T,I ε represents the distance vector from the center of the signal transmitting end to the center of the smart reflective surface. I,R (t) represents the distance vector from the center of the intelligent reflective surface to the center of the signal receiver, x I The x-coordinate of the intelligent reflective surface is represented by the x-coordinate on the x-axis, and the y-coordinate by the y-coordinate. I H represents the y-coordinate of the intelligent reflective surface on the y-axis. IRS H represents the height of the intelligent reflective surface. BS This indicates the height of the signal transmitting end. This represents the distance vector from the first antenna element to the p-th antenna element in the uniform linear antenna array of the signal transmitter. This represents the distance vector from the first antenna element to the qth antenna element in the uniform linear antenna array of the signal receiver. Let D represent the distance vector from the center of the intelligent reflective surface to the nth reflecting unit of the intelligent reflective surface, and let v represent the initial distance between the signal receiver and the signal transmitter. R χ represents the moving speed of the signal receiver. R The x represents the horizontal motion angle of the signal receiving end. I y I ε T,I ε I,R (t), H IRS H BS , D、v R and χ R All parameters are known, x I y I ε T,I ε I,R (t), H IRS H BS And D are determined based on the channel model; Based on the first formula, the second formula, the third formula, the fourth formula, and the fifth formula, the first sub-dynamic phase of the nth reflecting unit of the smart reflective surface is calculated using the sixth formula, wherein the sixth formula is: in, This represents the first sub-dynamic phase of the nth reflecting unit of the intelligent reflective surface after a preset time interval, where Δt represents the preset time interval. This represents the distance from the nth reflecting unit of the intelligent reflective surface to the signal receiving end after a preset time interval; The first sub-predicted phase of the nth reflective unit of the smart reflective surface after a preset time interval is calculated using the seventh formula and the eighth formula, wherein the seventh formula and the eighth formula are respectively: in, This represents the first sub-predicted phase of the nth reflective unit of the smart reflective surface after a preset time interval. This indicates the phase that needs to be adjusted for the nth reflecting unit of the smart reflective surface after a preset time interval. It is determined based on the Taylor expansion method; The second sub-initial phase of the nth reflective unit of the airborne intelligent reflective surface is calculated using the following formulas: the ninth formula, the tenth formula, the eleventh formula, the twelfth formula, and the thirteenth formula, respectively: ε T,A (t)=[x A (t),y A (t),z A (t)] T , in, This represents the second sub-initial phase of the nth reflecting unit of the aerial intelligent reflector. This represents the distance vector from the signal transmitter to the nth reflecting unit of the airborne intelligent reflector. ε represents the distance vector from the nth reflecting unit of the aerial intelligent reflector to the signal receiver. T,A (t) represents the distance vector from the center of the signal transmitter to the center of the airborne intelligent reflector, ε A,R (t) represents the distance vector from the center of the airborne intelligent reflector to the center of the signal receiver, x A (t) represents the x-coordinate of the intelligent aerial reflector on the x-axis, y A (t) represents the ordinate of the aerial intelligent reflective surface on the y-axis, z A (t) represents the vertical coordinate of the aerial intelligent reflective surface on the z-axis, H AIRS This indicates the height of the aerial intelligent reflective surface. Let x represent the distance vector from the center of the airborne intelligent reflector to the nth reflecting unit of the airborne intelligent reflector. A (t), y A (t), z A (t), ε T,A (t), ε A,R (t), H AIRS , D、v R and χ R All parameters are known, x A (t), y A (t), z A (t), ε T,A (t), ε A,R (t), H AIRS And D are determined based on the channel model; Based on the ninth, tenth, eleventh, twelfth, and thirteenth formulas, the second sub-dynamic phase of the nth reflective unit of the aerial intelligent reflective surface after a preset time interval is calculated using the fourteenth formula, wherein the fourteenth formula is: in, This represents the first sub-dynamic phase of the nth reflective unit of the aerial intelligent reflective surface after a preset time interval, where Δt represents the preset time interval. This represents the distance vector from the signal transmitter to the nth reflecting unit of the airborne intelligent reflector after a preset time interval. This represents the distance vector from the nth reflecting unit of the intelligent aerial reflector to the signal receiver after a preset time interval. The second sub-predicted phase of the nth reflective unit of the aerial intelligent reflective surface is calculated using formulas fifteen and sixteen after a preset time interval, wherein formulas fifteen and sixteen are respectively: in, This represents the second sub-predicted phase of the nth reflective unit of the aerial intelligent reflective surface after a preset time interval. This indicates the phase that needs to be adjusted for the nth reflecting unit of the aerial intelligent reflector after a preset time interval. It is determined based on the Taylor expansion method.

4. The method according to claim 2, characterized in that, The method further includes: Based on the channel model, the phase information of the smart reflector, the phase information of the airborne smart reflector, the phase information of at least one of the scatterers, the motion information of the airborne smart reflector, and the motion information of the signal receiver, the channel impulse response of the signal transmitter and the signal receiver is calculated using the following seventeenth formula. The channel impulse response of the signal transmitter and the signal receiver includes the channel impulse response of the smart reflector diameter, the channel impulse response of the airborne smart reflector diameter, and the channel impulse response of a single-hop path. The seventeenth formula is: Among them, h pq (t,τ) represents the channel impulse response of the signal transmitter and the signal receiver. This represents the channel impulse response of the intelligent reflector diameter. This represents the channel impulse response of the aforementioned airborne intelligent reflector diameter. The channel impulse response of the single-hop path is represented by t, where t represents time and τ represents time delay.

5. The method according to claim 4, characterized in that, The method further includes: Based on the channel model, the phase information of the smart reflector, and the motion information of the signal receiver, the channel impulse response of the smart reflector diameter is determined and calculated using the following eighteenth formula, wherein the eighteenth formula is: Among them, K Rice The sum of the Rice factors of the airborne intelligent reflector diameter and the intelligent reflector diameter is used to determine power distribution, K. Rice =K IRS +K AIRS K AIRS K represents the Rice factor of the aerial intelligent reflector diameter. IRS The Rice factor, n, represents the diameter of the intelligent reflective surface. i N represents the nth reflecting unit of the intelligent reflecting surface. IRS The total number of reflective units of the intelligent reflective surface diameter. This represents the first sub-initial phase of the nth reflecting unit of the intelligent reflective surface, where j is the imaginary unit and λ represents the wavelength. This represents the distance from the signal transmitter to the nth reflecting unit of the smart reflective surface. v represents the distance from the nth reflecting unit of the intelligent reflective surface to the signal receiving end. R The speed of the signal receiver is represented by t, where t represents time. This indicates the orientation angle between the signal receiver and the smart reflector. χ represents the elevation angle between the signal receiver and the smart reflector. R τ represents the horizontal motion angle of the signal receiving end. IRS (t) represents the time delay of the intelligent reflective surface after propagation through the channel, and δ(·) represents the impulse function, δ(τ-τ IRS (t) represents the channel impulse response of the intelligent reflective surface diameter.

6. The method according to claim 4, characterized in that, The method further includes: Based on the channel model, the phase information of the airborne smart reflector, the motion information of the airborne smart reflector, and the motion information of the signal receiver, the channel impulse response of the airborne smart reflector is calculated using the following nineteenth formula, wherein the nineteenth formula is: Among them, K Rice The sum of the Rice factors of the airborne intelligent reflector diameter and the intelligent reflector diameter is used to determine power distribution, K. Rice =K IRS +K AIRS K AIRS K represents the Rice factor of the aerial intelligent reflector diameter. IRS The Rice factor, n, represents the diameter of the intelligent reflective surface. a N represents the nth reflecting unit of the aerial intelligent reflective surface. AIRS The total number of reflective units of the aforementioned intelligent aerial reflective surface diameter. This represents the second sub-initial phase of the nth reflecting unit of the aerial intelligent reflector, where j is the imaginary unit and λ represents the wavelength. This represents the distance from the signal transmitter to the nth reflecting unit of the airborne intelligent reflector. The distance from the nth reflecting unit of the aerial intelligent reflector to the signal receiver is represented by t, where t represents time, and v is the distance from the nth reflecting unit of the aerial intelligent reflector to the signal receiver. A v represents the moving speed of the aerial intelligent reflector. R This indicates the moving speed of the signal receiver. This indicates the azimuth angle between the signal transmitter and the airborne intelligent reflector. This indicates the elevation angle between the signal transmitter and the airborne intelligent reflector. This indicates the azimuth angle between the signal receiver and the aerial intelligent reflector. This indicates the elevation angle between the signal receiver and the aerial smart reflector. This indicates the horizontal motion angle of the aforementioned aerial intelligent reflector. χ represents the vertical motion angle of the aforementioned aerial intelligent reflector. R τ represents the horizontal motion angle of the signal receiving end. AIRS The time delay of the airborne intelligent reflector after propagation through the channel is represented by δ(·), and δ(τ-τ) represents the impulse function. AIRS (t) represents the channel impulse response of the airborne intelligent reflector.

7. The method according to claim 4, characterized in that, The method further includes: Based on the channel model, the phase information of at least one of the scatterers, and the motion information of the signal receiver, the channel impulse response of the single-hop path is calculated using the following twentieth formula, wherein the twentieth formula is: Among them, K Rice The sum of the Rice factors of the airborne intelligent reflector diameter and the intelligent reflector diameter is used to determine power distribution, K. Rice =K IRS +K AIRS K AIRS K represents the Rice factor of the aerial intelligent reflector diameter. IRS The Rice factor representing the diameter of the intelligent reflective surface, wherein there are multiple scatterers, which are divided into clusters, and each cluster includes at least one scatterer, P (c) (t) represents the total power of each cluster of scatterers, C represents the total number of clusters, and M represents the number of scatterers in each cluster. This represents the random phase of the m-th scatterer in the c-th cluster. This represents the distance from the signal transmitter to the m-th scatterer in the c-th cluster. This represents the distance from the m-th scatterer in the c-th cluster to the signal receiver. This represents the directional angle between the signal receiver and the m-th scatterer in the c-th cluster. This represents the elevation angle between the signal receiver and the m-th scatterer of the c-th cluster. The time delay of the c-th cluster scatterer propagating through the channel is represented by δ(·), and δ(·) represents the impulse function. This represents the channel impulse response of a single hop path.

8. A multi-intelligent reflector phase design device based on a channel model, characterized in that, include: The module is configured to establish a channel model for the signal transmitter and the signal receiver based on the location information of the signal transmitter, the location information of the signal receiver, the location information of the smart reflector, the location information of the airborne smart reflector, and the location information of at least one scatterer. The calculation module is configured to calculate the first initial phase and the first dynamic phase after a preset time interval of the smart reflector based on the channel model and the motion information of the signal receiver. Based on the channel model, the motion information of the airborne intelligent reflector, and the motion information of the signal receiver, the second initial phase of the airborne intelligent reflector and the second dynamic phase after the preset time interval are calculated respectively. The calculation module is also configured to calculate the first predicted phase of the smart reflector after the preset time interval based on the first initial phase, and to calculate the second predicted phase of the airborne smart reflector after the preset time interval based on the second initial phase; The judgment module is configured to determine the first predicted phase as the first target phase of the intelligent reflector after the preset time interval if the error tolerance of the first predicted phase and the first dynamic phase meets the first preset error tolerance; and to determine the second predicted phase as the second target phase of the airborne intelligent reflector after the preset time interval if the error tolerance of the second predicted phase and the second dynamic phase meets the second preset error tolerance.

9. An electronic device, characterized in that, include: At least one processor; Memory for storing the at least one processor-executable instruction; The at least one processor is configured to execute the instructions to implement the steps of the method as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, When the instructions in the computer-readable storage medium are executed by the processor of the electronic device, the electronic device is enabled to perform the steps of the method as described in any one of claims 1 to 7.

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