A single-hop FSO communication method and device based on unmanned aerial vehicle relay and storage medium

Abstract

The application relates to a single-hop FSO communication method based on unmanned aerial vehicle relaying, a device and a storage medium, and belongs to the technical field of wireless optical communication. The application comprises the following steps: constructing an atmospheric turbulence loss, a path fading loss and an alignment loss model; obtaining information of a transmitting end, a receiving end and an obstacle, and establishing a single-hop FSO communication system model under the optimal elevation angle of an unmanned aerial vehicle; obtaining the functional relationship between the unmanned aerial vehicle relaying position under the optimal elevation angle and the overall channel signal-to-noise ratio; solving the functional relationship to obtain the position with the maximum overall channel signal-to-noise ratio as the optimal unmanned aerial vehicle relaying position. The application focuses on the phenomenon that the overall channel signal-to-noise ratio is different due to the difference in the hovering position of the unmanned aerial vehicle in the single-hop FSO communication process of the unmanned aerial vehicle relaying. Through in-depth analysis and research on the overall channel signal-to-noise ratio, the optimal unmanned aerial vehicle relaying position is accurately calculated, the influence of the shielding object can be avoided, the system performance can be optimized and improved, and a solid foundation is laid for efficient and stable communication.

Description

Technical Field

[0001] This invention relates to a single-hop FSO communication method, device, and storage medium based on UAV relay, belonging to the field of wireless optical communication technology. Background Technology

[0002] Free-space optical communication (FSO), a broadband wireless optical communication technology that uses lasers for data transmission, exhibits numerous significant technological advantages compared to traditional radio frequency (RF) communication. Its optical bandwidth is extremely wide, achieving high-speed transmission rates of 100Gbps and above through wavelength division multiplexing (WDM) technology, meeting the demands of rapid data transmission. It also possesses excellent resistance to electromagnetic interference, making it particularly suitable for areas where wireless RF communication is strictly prohibited and in environments with strong electromagnetic fields. Furthermore, its spectrum resources do not require special application, and the narrow laser beam with good directionality and excellent confidentiality effectively protects the security and privacy of communication content.

[0003] However, the beam emitted by FSO communication is highly susceptible to interference and influence from weather and the external environment, severely limiting its transmission distance. Currently, repeaters are often used to overcome this limitation. However, most of these repeaters are fixed, making it impossible to flexibly find the optimal communication location based on the channel environment. Furthermore, FSO communication is line-of-sight communication, and various obstructions are inevitable in the transmission channel, severely restricting its application scenarios.

[0004] Some scholars have proposed using drones as communication relays to achieve mobile relay. However, when drones are used as communication relay nodes, the path fading loss will change accordingly due to the change in their location, which will have a significant impact on the communication performance of the entire system. Summary of the Invention

[0005] The purpose of this invention is to overcome the shortcomings of the prior art and provide a single-hop FSO communication method based on UAV relay, which solves the problem of poor communication performance of UAV relay communication under non-line-of-sight conditions.

[0006] To achieve the above objectives, the present invention is implemented using the following technical solution:

[0007] In a first aspect, the present invention provides a single-hop FSO communication method based on UAV relay, comprising:

[0008] S1: Construct a channel loss model, including: an atmospheric turbulence loss model, a path fading loss model, and an alignment loss model; wherein, the atmospheric turbulence loss and alignment loss are independent of the communication path distance, while the path fading loss is related to the communication path distance.

[0009] S2: Acquire information about the transmitter, receiver, and obstacles, and establish a single-hop FSO communication system model for the UAV at the optimal elevation angle;

[0010] S3: Based on the single-hop FSO communication system model and channel loss model, obtain the functional relationship between the UAV relay position and the overall channel signal-to-noise ratio at the optimal elevation angle;

[0011] S4: Solve the aforementioned functional relationship to obtain the position with the highest overall channel signal-to-noise ratio, which will be used as the optimal relay position for the UAV.

[0012] Furthermore, both the transmitting and receiving ends are equipped with bidirectional photodetectors to convert the received optical signals into electrical signals; the UAV is equipped with a bidirectional photodetector with amplification function to amplify the optical signals before converting them into electrical signals; the transmitting end, the UAV, and the receiving end are all equipped with acquisition, tracking, and pointing devices to achieve alignment at both ends.

[0013] Furthermore, the path fading loss model is as follows: ; In the formula, For path fading loss, This represents the communication path distance.

[0014] Furthermore, a single-hop FSO communication system model is established for the UAV at the optimal elevation angle, including:

[0015] S21: Construct the physical architecture of the communication system, including: the sending end as the source node for information transmission, denoted as A; the receiving end as the destination node, denoted as B; and the UAV as a relay node, denoted as C; where A and B are fixed nodes, and C is a mobile node; the horizontal distance between the sending end A and the receiving end B is... The height difference between the transmitter A and the receiver B is The elevation angle of the highest point of the obstacle to transmitter A is... ;

[0016] S22: Elevation Angle The optimal elevation angle is determined to minimize path fading loss; and the horizontal distance between transmitter A and UAV C is denoted as... ;

[0017] S23: Establish a single-hop FSO communication system model, wherein the communication path of the single-hop FSO communication system model includes: the first path from the transmitter A to the UAV C and the second path from the UAV C to the receiver B;

[0018] The communication path distance between the first path and the second path is: ; ;

[0019] The signal received by the drone relay is: ;

[0020] The signal received is: ; in, ; ; In the formula, In order to transmit signals, The signal received by the drone relay. The signal received by the receiving end. The responsivity of the bidirectional photodetector on the UAV. This represents the total loss of the first path. This represents the noise of the first path. For the responsivity of the bidirectional photodetector at the receiving end, This represents the total loss along the second path. To amplify the gain, This is second-path noise; The atmospheric turbulence loss for the first path, For the alignment loss of the first path, The atmospheric turbulence loss for the second path, This represents the alignment loss of the second path.

[0021] Furthermore, the functional relationship between the UAV relay position at the optimal elevation angle and the overall channel signal-to-noise ratio is obtained, including:

[0022] Obtain the signal-to-noise ratio of the first path Signal-to-noise ratio of the second path The expression is: ; ; In the formula, The average power of the first path, This represents the noise power of the first path. The average power of the second path; This represents the noise power of the second path;

[0023] Obtain the overall channel signal-to-noise ratio Regarding the signal-to-noise ratio of the first path Second path signal-to-noise ratio The expression: ;

[0024] Obtain the overall channel signal-to-noise ratio Regarding the horizontal distance between the transmitter and the drone The expression: ;

[0025] Furthermore, the atmospheric turbulence loss model adopts Turbulence model or Gamma-Gamma distribution characterization.

[0026] Furthermore, the noise in both the first and second paths is additive white Gaussian noise;

[0027] use When characterizing atmospheric turbulence loss models using turbulence models, the Mayer function is used to represent the first... The probability density function of path signal-to-noise ratio; ; in, ; ; ; ; ; In the formula, , The standard deviation of additive white Gaussian noise. It is related to the effective number of large-scale scattering units. This refers to the scattered component received off-axis. The scattered power coupled to the line-of-sight transmission component, The average power of the total scattered quantity For the number of decays, The average power of the coherent signal. Bessel function Category II Gamma function of order, As the first intermediate quantity, As the second intermediate quantity, It is the third intermediate quantity.

[0028] Furthermore, in the alignment loss model, alignment loss The probability density function is: ; In the formula, The incident angle of the bidirectional photodetector on the UAV. The distance from the transmission center to the beam center. for variance Distance Beam width at that location, Let be the radius of the circular receiving area on the bidirectional photodetector.

[0029] In a second aspect, the present invention provides an electronic device, comprising: a processor and a memory; the memory stores computer-readable instructions, which, when executed by the processor, implement the single-hop FSO communication method based on UAV relay as described in the first aspect.

[0030] Thirdly, the present invention provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the single-hop FSO communication method based on UAV relay as described in the first aspect.

[0031] Compared with the prior art, the beneficial effects achieved by the present invention are as follows: (1) This invention, through in-depth analysis and research on the overall channel signal-to-noise ratio, accurately calculates the optimal UAV relay position, which can avoid the influence of obstructions and also optimize and improve system performance, laying a solid foundation for efficient and stable communication. (2) This invention increases the transmitted optical signal by adding an optical amplifier, which helps to realize remote communication, effectively solves the problem of line-of-sight communication, and greatly extends the application scope of FSO. (3) When optical cables between important nodes are blocked and there is an urgent need to build communication links, the present invention relies on drones to quickly build an end-to-end communication network and adjust the channel transmission performance to the best state. Attached Figure Description

[0032] Figure 1 This is a flowchart of the single-hop FSO communication method based on UAV relay provided in Embodiment 1 of the present invention;

[0033] Figure 2 This is a schematic diagram of the single-hop FSO communication system model provided in Embodiment 1 of the present invention;

[0034] Figure 3 This is a schematic diagram of bidirectional communication in the single-hop FSO communication system provided in Embodiment 1 of the present invention. Detailed Implementation

[0035] The terms "comprising" and "having," and any variations thereof, in the specification, claims, and accompanying drawings of this application are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or apparatus that includes a series of steps or units is not necessarily limited to those explicitly listed, but may include other steps or units not explicitly listed or inherent to these processes, methods, products, or apparatuses. The technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them.

[0036] Free-space optical communication (FSO) offers advantages such as high bandwidth, ease of deployment, high security, and cost-effectiveness, making it an effective solution for terrestrial, airborne, and satellite networks. However, the transmission performance of FSO is limited by factors such as geometric loss, pointing error, atmospheric attenuation, and turbulence.

[0037] Example 1

[0038] This embodiment provides a single-hop FSO communication method based on UAV relay, such as... Figure 1 As shown, this method includes the following steps:

[0039] Step 1: Construct a channel loss model, including: atmospheric turbulence loss model, path fading loss model, and alignment loss model.

[0040] As is well known, atmospheric turbulence refers to the random changes in local atmospheric temperature and pressure, and the random fluctuations in atmospheric refractive index, which cause changes in light intensity and phase in space and time during light transmission, resulting in phase distortion, light intensity flicker, etc. It mainly occurs at the boundary of several airflow layers moving at different speeds. It can be seen that the magnitude of atmospheric turbulence loss is affected by atmospheric conditions.

[0041] The atmospheric environment is far from an ideal vacuum; it is filled with various complex media and variable weather conditions. These factors intertwine to create "energy traps" in the transmission of optical signals. Furthermore, the atmosphere itself possesses absorption properties, converting some of the energy of the optical signal into heat and dissipating it. Therefore, path fading loss is introduced to describe the amount of loss in the propagation environment between the transmitter and receiver. Path fading loss is only related to the propagation path; the longer the path, the greater the path loss.

[0042] Alignment loss is a significant factor in the operation of optical communication systems, and one of its main causes is photodetector misalignment. As a crucial component for optical signal reception, even slight changes in the position of the photodetector can affect the accurate reception of optical signals. Similarly, the hovering and shaking of drones can also cause alignment loss issues in optical communication.

[0043] Therefore, this invention establishes three models to describe atmospheric turbulence loss, path fading loss, and alignment loss in a single-hop FSO communication transmission system. The models for atmospheric turbulence loss and alignment loss are independent of the communication path distance variable, while the model for path fading loss is related to the communication path distance variable.

[0044] In existing technologies, common path fading loss models are as follows: ; In the formula, For path fading loss, For communication path distance, This represents the fading coefficient.

[0045] For the common path fading loss models mentioned above, under clear weather conditions... Therefore, in this embodiment, the path fading loss model is set to 1: ;

[0046] In some specific embodiments, the atmospheric turbulence loss model adopts Turbulence model or Gamma-Gamma distribution characterization.

[0047] Step 2: Obtain information on the transmitter, receiver, and obstacles, and establish a single-hop FSO communication system model under the optimal elevation angle of the UAV.

[0048] like Figure 2 As shown, the FSO transmitter and receiver have fixed positions and heights, but there is a height difference and an obstruction in between, making line-of-sight communication impossible. A UAV is deployed between the two as a relay to construct a single-hop FSO communication system model for transmitting, relaying, and receiving under non-line-of-sight conditions.

[0049] It should be noted that this invention is applicable to situations where the distance between the transmitter and receiver meets the requirements for normal single-hop FSO communication, and multi-hop relay is not required using a UAV.

[0050] Specifically, first construct the physical architecture of the communication system, such as Figure 2 As shown, the sending end, denoted as A, is the source node for information transmission; the receiving end, denoted as B, is the destination node; and the UAV, denoted as C, is the relay node. A and B are fixed nodes, and C is a mobile node. The horizontal distance between sending end A and receiving end B is... The height difference between the transmitter A and the receiver B is The elevation angle of the highest point of the obstacle to transmitter A is... .

[0051] To minimize path fading loss, the elevation angle will be... Determine the optimal elevation angle for drone deployment. Also determine the horizontal distance between transmitter A and drone C. Set as the independent variable.

[0052] In addition, both the transmitting and receiving ends are equipped with bidirectional photodetectors to convert the received optical signals into electrical signals. The drone used for relaying is a hovering drone equipped with a bidirectional photodetector with amplification function, which amplifies the optical signal before converting it into an electrical signal.

[0053] The transmitter, drone, and receiver are all equipped with Acquisition, Tracking, and Pointing (ATP) devices, enabling 360° horizontal and 90° vertical rotation for easy alignment at both ends.

[0054] The optical amplifier of the relay drone adopts the amplification and relay mode, the bidirectional photodetector uses intensity detection / direct detection, and the modulation method uses on / off key control.

[0055] The communication between the transmitter, the drone, and the receiver is bidirectional.

[0056] Specifically, such as Figure 3 As shown, when transmitter A sends an optical signal to receiver B, the wavelength is... The optical signal is transmitted to the relay UAV C via the FSO channel. The photodetector at the C end converts the received optical signal into an electrical signal, amplifies the signal, and then converts it into a wavelength of... The optical signal is transmitted to receiver B through the FSO channel.

[0057] When receiver B sends an optical signal to transmitter A, the wavelength is The optical signal is transmitted to the relay UAV C via the FSO channel. The photodetector at the C end converts the received optical signal into an electrical signal, amplifies the signal, and then converts it into a wavelength of... The optical signal is transmitted to the transmitter A through the FSO channel.

[0058] A single-hop FSO communication model is established, wherein the communication path of the single-hop FSO communication model includes: the first path from the transmitter A to the UAV C and the second path from the UAV C to the receiver B.

[0059] according to Figure 2 The communication path distance between the first path and the second path in the single-hop FSO communication system model shown is: ; ;

[0060] The signal received by the drone relay is: ;

[0061] The signal received is: ; in, ; ; In the formula, In order to transmit signals, The signal received by the drone relay. The signal received by the receiving end. The responsivity of the bidirectional photodetector on the UAV. This represents the total loss of the first path. This represents the noise of the first path. For the responsivity of the bidirectional photodetector at the receiving end, This represents the total loss along the second path. To amplify the gain, This is second-path noise; The atmospheric turbulence loss for the first path, For the alignment loss of the first path, The atmospheric turbulence loss for the second path, This represents the alignment loss of the second path.

[0062] As can be seen from the above single-hop FSO communication system model, when the UAV's position changes, the path fading loss will change accordingly, affecting the performance of the entire FSO communication system.

[0063] Step 3: Based on the single-hop FSO communication system model and channel loss model, obtain the functional relationship between the UAV relay position at the optimal elevation angle and the overall channel signal-to-noise ratio, including:

[0064] Step 31: Obtain the signal-to-noise ratio of the first path Signal-to-noise ratio of the second path The expression is: ; ; In the formula, The average power of the first path, This represents the noise power of the first path. The average power of the second path; This represents the noise power of the second path.

[0065] Step 32: Obtain the overall channel signal-to-noise ratio Regarding the signal-to-noise ratio of the first path Second path signal-to-noise ratio The expression: ;

[0066] Specifically, the overall channel signal-to-noise ratio Regarding the signal-to-noise ratio of the first path Second path signal-to-noise ratio The process of obtaining the expression is as follows:

[0067] The instantaneous signal-to-noise ratio of the entire system can be calculated using the following formula: ; in: ;

[0068] Combination and The expression can be deduced as follows about and General expression: ;

[0069] In cases with high signal-to-noise ratio, the digit 1 can be omitted, thus obtaining the above result. about and The expression.

[0070] Step 33: Obtain the overall channel signal-to-noise ratio Regarding the horizontal distance between the transmitter and the drone The expression: ;

[0071] Thus, at the optimal elevation angle, the overall channel signal-to-noise ratio is obtained with respect to the independent variable, the horizontal distance between the transmitter and the UAV. By solving the functional relationship, we can obtain the overall channel signal-to-noise ratio at the optimal elevation angle. The value represents the optimal relay location for the drone.

[0072] In this embodiment, based on the FSO transmission channel model, a comprehensive analysis is conducted on the deployment location of the UAV, the location of obstructions, the UAV's elevation angle, the characteristics of the transmission channel, and the intrinsic relationship between the transmitter and receiver. Using the signal-to-noise ratio (SNR) of the entire communication system as the evaluation standard, the mathematical relationship between the UAV deployment location and the SNR of the entire communication system is derived. By analyzing the mathematical relationship, the optimal UAV deployment location with the best SNR is determined, providing strong support and guarantee for the technological development in related fields.

[0073] Example 2

[0074] Based on Example 1, this example provides the construction of an atmospheric turbulence loss model and an alignment loss model.

[0075] When studying the impact of atmospheric turbulence on optical communication systems The distribution exhibits remarkable versatility, adaptable to both relatively stable, weakly turbulent environments with few interfering factors, and highly turbulent situations with violently churning air and complex, variable optical transmission environments. Distributed models can accurately characterize the optical signal fading characteristics caused by atmospheric turbulence, closely matching actual transmission conditions.

[0076] When focusing on the observation field at the receiver, three key components can be clearly deconstructed: the line-of-sight transmission component, the energy component scattered to the receiver, and the scattered component on the signal transmission axis, which are coupled with the line-of-sight transmission.

[0077] It should be noted that in this embodiment, the noise in the first path and the second path are both additive white Gaussian noise.

[0078] In some specific embodiments, the following are adopted: The turbulence model characterizes the atmospheric turbulence loss model, and the signal-to-noise ratio probability density function of the first and second paths is expressed by the Mayer function; ; in, ; ; ; ; ; In the formula, , The time describes the signal-to-noise ratio probability density function of the first path. The time describes the second path signal-to-noise ratio probability density function. The standard deviation of additive white Gaussian noise. It is related to the effective number of large-scale scattering units. This represents the scattered component received off-axis. The scattered power coupled to the line-of-sight transmission component, The average power of the total scattered quantity For the number of decays, The average power of the coherent signal. Bessel function Category II Gamma function of order, As the first intermediate quantity, As the second intermediate quantity, It is the third intermediate quantity.

[0079] In some specific embodiments, alignment loss The probability density function is: ; In the formula, The incident angle of the bidirectional photodetector on the UAV. The distance from the transmission center to the beam center. for variance Distance Beam width at that location, Let be the radius of the circular receiving area on the bidirectional photodetector.

[0080] Example 3

[0081] This embodiment provides an electronic device, including: a processor, a communication interface, a communication bus, and a memory; wherein, the processor, the communication interface, and the memory communicate with each other through the communication bus, the memory stores computer-readable instructions, and the processor can call the computer-readable instructions in the memory to execute the single-hop FSO communication method based on UAV relay as described in Embodiment 1 or Embodiment 2.

[0082] Furthermore, the computer-readable instructions in the aforementioned memory can be implemented as software functional units and sold or used as independent products, and can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention.

[0083] Example 4

[0084] This embodiment provides a computer-readable storage medium storing a computer program. When executed by a processor, the computer program implements the single-hop FSO communication method based on UAV relay as described in Embodiment 1 or Embodiment 2. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0085] The above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. A single-hop FSO communication method based on UAV relay, characterized in that, include: S1: Construct a channel loss model, including: an atmospheric turbulence loss model, a path fading loss model, and an alignment loss model; wherein, the atmospheric turbulence loss and alignment loss are independent of the communication path distance, while the path fading loss is related to the communication path distance. S2: Acquire information from the transmitter, receiver, and obstacles to establish a single-hop FSO communication system model for the UAV at the optimal elevation angle, including: S21: Construct the physical architecture of the communication system, including: the sending end as the source node for information transmission, denoted as A; the receiving end as the destination node, denoted as B; and the UAV as a relay node, denoted as C; where A and B are fixed nodes, and C is a mobile node; the horizontal distance between the sending end A and the receiving end B is... The height difference between the transmitter A and the receiver B is The elevation angle of the highest point of the obstacle to transmitter A is... ; S22: Elevation Angle The optimal elevation angle is determined to minimize path fading loss; and the horizontal distance between transmitter A and UAV C is denoted as... ; S23: Establish a single-hop FSO communication system model, wherein the communication path of the single-hop FSO communication system model includes: the first path from the transmitter A to the UAV C and the second path from the UAV C to the receiver B; The communication path distance between the first path and the second path is: ； ； The signal received by the drone relay is: ； The signal received is: ； in, ； ； In the formula, In order to transmit signals, The signal received by the drone relay. The signal received by the receiving end. For the responsivity of the detector on the drone, This represents the total loss of the first path. This represents the noise of the first path. For the responsivity of the receiver detector, This represents the total loss along the second path. To amplify the gain, This is second-path noise; The atmospheric turbulence loss for the first path, For the alignment loss of the first path, The atmospheric turbulence loss for the second path, This refers to the alignment loss of the second path; S3: Based on the single-hop FSO communication system model and channel loss model, obtain the functional relationship between the UAV relay position and the overall channel signal-to-noise ratio at the optimal elevation angle; S4: Solve the aforementioned functional relationship to obtain the position with the highest overall channel signal-to-noise ratio, which will be used as the optimal relay position for the UAV.

2. The single-hop FSO communication method based on UAV relay according to claim 1, characterized in that, Both the transmitting and receiving ends are equipped with bidirectional photodetectors to convert the received optical signals into electrical signals; the UAV is equipped with a bidirectional photodetector with amplification function to amplify the optical signals before converting them into electrical signals. The transmitting end, the drone, and the receiving end are all equipped with acquisition, tracking, and pointing devices to achieve alignment between the two ends.

3. The single-hop FSO communication method based on UAV relay according to claim 2, characterized in that, The path fading loss model is as follows: ； In the formula, For path fading loss, This represents the communication path distance.

4. The single-hop FSO communication method based on UAV relay according to claim 1, characterized in that, The functional relationship between obtaining the UAV relay position at the optimal elevation angle and the overall channel signal-to-noise ratio includes: Obtain the signal-to-noise ratio of the first path Signal-to-noise ratio of the second path The expression is: ； ； In the formula, The average power of the first path, This represents the noise power of the first path; The average power of the second path; This represents the noise power of the second path; Obtain the overall channel signal-to-noise ratio Regarding the signal-to-noise ratio of the first path Second path signal-to-noise ratio The expression: ； Obtain the overall channel signal-to-noise ratio Regarding the horizontal distance between the transmitter and the drone The expression: 。 5. The single-hop FSO communication method based on UAV relay according to claim 1, characterized in that, The atmospheric turbulence loss model adopts Turbulence model or Gamma-Gamma distribution characterization.

6. The single-hop FSO communication method based on UAV relay according to claim 5, characterized in that, The noise in both the first and second paths is additive white Gaussian noise; use When characterizing atmospheric turbulence loss models using turbulence models, the Mayer function is used to represent the first... The probability density function of path signal-to-noise ratio; ； in, ; ； ； ； ； In the formula, , The standard deviation of additive white Gaussian noise. It is related to the effective number of large-scale scattering units. This refers to the scattered component received off-axis. The scattered power coupled to the line-of-sight transmission component, The average power of the total scattered quantity For the number of decays, The average power of the coherent signal. For Bessel functions, Category II Gamma function of order, As the first intermediate quantity, As the second intermediate quantity, It is the third intermediate quantity.

7. The single-hop FSO communication method based on UAV relay according to claim 6, characterized in that, In the alignment loss model, alignment loss The probability density function is: ； In the formula, The incident angle of the bidirectional photodetector on the UAV. The distance from the transmission center to the beam center. for variance Distance Beam width at that location, Let be the radius of the circular receiving area on the bidirectional photodetector.

8. An electronic device, characterized in that, include: Processor and memory; The memory stores computer-readable instructions, which, when executed by the processor, implement the single-hop FSO communication method based on UAV relay according to any one of claims 1-7.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the single-hop FSO communication method based on UAV relay as described in any one of claims 1-7.

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