Unmanned aerial vehicle video stream code rate selection and time-frequency resource allocation method and system

Abstract

The invention discloses a code rate selection and time-frequency resource allocation method and system for a video stream of an unmanned aerial vehicle. According to the method, firstly, the distance between an unmanned aerial vehicle and a user is determined by obtaining position information of the unmanned aerial vehicle and the user; then, based on the position information and the distance, the channel gain between the unmanned aerial vehicle and the user under each time slot is calculated. The channel gains are then used to calculate the rate at which each user uses each channel in each time slot. On the basis, a proportional fair scheduling algorithm is adopted to determine the user priority corresponding to each channel and the video layer number of each user in each channel. And finally, according to the priorities and the number of video layers, carrying out user allocation on each channel until the signal-to-noise ratios of all users of each channel meet requirements. The method aims at optimizing the transmission efficiency and quality of the video stream of the unmanned aerial vehicle and improving the user experience.

Description

Technical Field

[0001] The invention belongs to the technical field of wireless video stream backhaul for unmanned aerial vehicles, and relates to a method and system for selecting bit rate and allocating time-frequency resources for video streaming for unmanned aerial vehicles. Background Art

[0002] With the rapid development of drone technology, the field of one-to-many drone communication, i.e. one-machine-multiple-control technology, has shown great potential and value in practical applications. This technology allows a single drone to be collaboratively controlled by multiple users, thus achieving a more efficient and flexible operation mode. Existing high-end drones have adopted multi-user control technology, allowing team members such as pilots, cameramen and directors to jointly operate a drone, greatly improving the efficiency of film and television production and industrial inspection.

[0003] In these advanced drone communication systems, real-time transmission of high-definition video and image data is one of the core functions. To achieve this, the system needs to support real-time monitoring and navigation by multiple users at the same time and ensure the real-time, stability and reliability of data transmission. However, the drone communication environment is relatively complex and spectrum resources are limited, which makes the allocation of bandwidth resources a key issue.

[0004] In practical applications, drone communications are subject to interference from multiple factors, such as terrain, ground obstruction, and noise generated by nature and human activities, which can lead to a decline in communication quality or even interruption. To solve this problem, researchers usually use dynamic resource allocation algorithms such as machine learning to optimize bandwidth resource allocation by tracking fluctuations in network conditions in real time. This dynamic allocation method can adjust the use of time and frequency resources in real time according to user needs and system status, thereby improving resource utilization and anti-interference capabilities.

[0005] On the other hand, Scalable Video Coding (SVC) technology is also widely used in drone data transmission to ensure the real-time and high-quality of video data. SVC technology can flexibly adjust the rate of the video layer according to channel feedback, allowing users to receive different numbers of enhancement layers according to different channel conditions, thereby ensuring the visual experience while improving the flexibility and adaptability of data transmission.

[0006] However, although SVC technology and dynamic resource allocation algorithms have achieved remarkable results in UAV communications, there are still some problems that need to be solved. For example, although the static resource allocation method is simple and direct, it has low resource utilization and weak anti-interference ability; while the dynamic resource allocation method can improve resource utilization, it requires more complex scheduling algorithms and signaling interactions, and may face the problem of poor user fairness in practical applications. Summary of the invention

[0007] The purpose of the present invention is to solve the technical problems in the prior art of SVC technology and dynamic resource allocation algorithm, such as weak anti-interference ability of static resource allocation, high complexity of dynamic resource allocation scheduling algorithm, and poor user fairness in UAV communication system, and to provide a method and system for selecting bit rate and allocating time-frequency resources for UAV video streaming.

[0008] In order to achieve the above object, the present invention adopts the following technical solutions: The first aspect of the present invention provides a method for selecting bit rate and allocating time-frequency resources for streaming unmanned aerial vehicle video, comprising the following steps: S1, obtain the location information of the drone and the user, and determine the distance between the drone and the user; S2, based on the distance between the drone and the user and the location information of the drone and the user, calculate the channel gain between the drone and the user in each time slot; S3, based on the channel gain between the drone and the user in each time slot, calculate the rate at which each user uses each channel in each time slot; based on the rate at which each user uses each channel in each time slot, use the proportional fair scheduling algorithm to determine the user priority corresponding to each channel and the number of video layers for each user in each channel; S4, based on the user priority corresponding to each channel and the number of video layers of each user in each channel, assign users to each channel until the signal-to-noise ratio of all users in each channel meets the requirements.

[0009] Furthermore, the distance between the drone and the user is described as:

[0010] in, For drones Always The coordinates of the axes; Indicates that the drone is Always The coordinates of the axes; Indicates that the drone is Always The coordinates of the axis.

[0011] Furthermore, the channel gain between the drone and the user in each time slot is:

[0012] in, is a random variable representing the small-scale fading coefficient of the communication channel; is the path loss from the drone to the user signal:

[0013] in, is the carrier frequency; is the speed of light; express The distance between the drone and the user at any given moment.

[0014] Furthermore, the rate at which each user uses each channel in each time slot is:

[0015] in, For time slot t Next u Users use m The rate of the channels; B For the m The bandwidth of the channel; M is the total number of channels; For the Users in time slot Use the The signal-to-noise ratio of a channel.

[0016] Furthermore, based on the rate at which each user uses each channel in each time slot, a proportional fair scheduling algorithm is used to determine the user priority corresponding to each channel and the number of video layers of each user in each channel, specifically: According to the rate at which each user uses each channel in each time slot, the sum of the rates of each user in all channels in each time slot is obtained; Based on the sum of the rates of each user in all channels in each time slot, select the number of video layers for each user in each channel; Based on the rate at which each user uses each channel in each time slot, a proportional fair scheduling algorithm is used to find the user priority corresponding to each channel.

[0017] Furthermore, the allocation of users to each channel is specifically as follows:

[0018] in, is the balance coefficient; is the variance of the average rate of each user and the total average rate of all users; For the The number of video layers per user; L is the total number of video layers.

[0019] Further, the

[0020] in, , represents the total average rate of all users; U is the total number of users; For the u Users in front t The average rate within a time slot.

[0021] Furthermore, the signal-to-noise ratio of all users of each channel meets the requirements, specifically:

[0022] in, For the u The signal power received by each user from the drone to other users; For the time slot Neidi The subchannels are assigned to the Channel indicators for each user; for t Drones and the Channel gain between users; For the i The received power of each user.

[0023] A second aspect of the present invention provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, it implements the above-mentioned method of bit rate selection and time-frequency resource allocation for drone video streaming.

[0024] The third aspect of the present invention provides a bit rate selection and time-frequency resource allocation system for unmanned aerial vehicle video streaming, comprising: The location determination module obtains the location information of the drone and the user and determines the distance between the drone and the user; The channel gain calculation module calculates the channel gain between the drone and the user in each time slot based on the distance between the drone and the user and the location information of the drone and the user; The priority scheduling module calculates the rate at which each user uses each channel in each time slot based on the channel gain between the drone and the user in each time slot. Based on the rate at which each user uses each channel in each time slot, the proportional fair scheduling algorithm is used to determine the user priority corresponding to each channel and the number of video layers for each user in each channel. The resource allocation module allocates users to each channel based on the user priority corresponding to each channel and the number of video layers of each user in each channel until the signal-to-noise ratio of all users in each channel meets the requirements.

[0025] Compared with the prior art, the present invention has the following beneficial effects: The present invention discloses a method for selecting a bit rate and allocating time-frequency resources for streaming video from a drone. By acquiring the location information of a drone and a user in real time and determining the distance between the drone and the user accordingly, the present invention can dynamically adjust the transmission strategy to ensure stable transmission of video streams at different distances. Based on the calculation of channel gain, the present invention can accurately evaluate the communication quality between the drone and the user in each time slot, thereby optimizing the bit rate selection and resource allocation, effectively reducing the bit error rate in transmission, and improving the clarity and fluency of the video stream. The present invention adopts a proportional fair scheduling algorithm to dynamically adjust the user priority and the number of video layers according to the rate at which each user uses each channel in each time slot, thereby ensuring the fairness and efficiency of resource allocation. The transmission strategy can be flexibly adjusted according to the actual needs and network conditions of different users, effectively responding to complex and changeable communication environments, and improving the overall performance of the system. Through the fine management of users assigned to each channel, the present invention ensures that the signal-to-noise ratio of all users in each channel meets the requirements, avoiding waste and conflict of resources. The method can make full use of limited time-frequency resources, achieve optimal resource allocation, and improve the throughput and spectrum efficiency of the system. This method can also dynamically adjust the number of video layers and bit rates according to the user's actual needs and network conditions to meet the user's different needs for video quality.

[0026] Furthermore, by calculating the sum of the rates of each user in all channels in each time slot, data support is provided for the selection of the number of video layers. This refined calculation method ensures the rationality and efficiency of resource allocation, so that each user can obtain the most suitable number of video layers according to its own transmission needs and channel conditions, thereby maximizing resource utilization while ensuring video quality. The proportional fair scheduling algorithm is adopted to dynamically adjust the user priority according to the rate of each user using each channel in each time slot. This strategy not only considers the user's instantaneous transmission rate, but also takes into account long-term fairness. It ensures that all users can obtain relatively fair resource allocation opportunities and avoids unfair resource allocation caused by fluctuations in transmission rate within a single time slot. By calculating the transmission rate in each time slot in real time and adjusting the user priority and the number of video layers accordingly, the system can quickly adapt to changes in the network environment. Whether it is fluctuations in channel quality or changes in user needs, the system can respond through flexible scheduling strategies, thereby enhancing the system's adaptability and robustness. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the embodiments are briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without creative work.

[0028] Figure 1 This is a scene diagram of the drone video transmission in an embodiment of the present invention; Figure 2 This is a flow chart of a method for selecting bit rate and allocating time-frequency resources for video streaming by unmanned aerial vehicles according to an embodiment of the present invention; Figure 3 For time slot t Diagram of the iterative process of calculating the average transmission rate; Figure 4 This is the flow chart of the proportional fair scheduling algorithm. DETAILED DESCRIPTION

[0029] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. The components of the embodiments of the present invention described and marked in the drawings here can be arranged and designed in various different configurations.

[0030] Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the invention claimed for protection, but merely represents selected embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0031] It should be noted that similar reference numerals and letters denote similar items in the following drawings, and therefore, once an item is defined in one drawing, further definition and explanation thereof is not required in subsequent drawings.

[0032] In the description of the embodiments of the present invention, it should be noted that if the terms "upper", "lower", "horizontal", "inner", etc. indicate an orientation or positional relationship based on the orientation or positional relationship shown in the drawings, or the orientation or positional relationship in which the product of the invention is usually placed when in use, it is only for the convenience of describing the present invention and simplifying the description, and does not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on the present invention. In addition, the terms "first", "second", etc. are only used to distinguish the description, and cannot be understood as indicating or implying relative importance.

[0033] In addition, if the term "horizontal" appears, it does not mean that the component must be absolutely horizontal, but can be slightly tilted. For example, "horizontal" only means that its direction is more horizontal than "vertical", which does not mean that the structure must be completely horizontal, but can be slightly tilted.

[0034] In the description of the embodiments of the present invention, it is also necessary to explain that, unless otherwise clearly specified and limited, the terms "set", "install", "connect", and "connect" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal connection of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0035] The present invention is further described in detail below in conjunction with the accompanying drawings: The present invention discloses a method for selecting a bit rate and allocating time-frequency resources for video streaming of an unmanned aerial vehicle, comprising the following steps: S1, obtain the location information of the drone and the user, determine the distance between the drone and the user; based on the distance between the drone and the user and the location information of the drone and the user, calculate the channel gain between the drone and each user in each time slot; See also Figure 1 ,When the drone video is streaming back ,the drone will transmit the captured video to each user during the flight. ,According to the user’s channel conditions and the user’s ,requirements for video quality, the number of video transmission layers is ,selected for the user to ensure the real-time transmission. ,The drone is controlled by one of the users.

[0036] In a scenario with a drone and multiple users, the user set is denoted as , both the drone and the user are equipped with omnidirectional antennas, and the time slot is divided into time slots, denoted as a set , the total bandwidth of all users Divide into sub-channels, denoted as a set , the bandwidth of each sub-band is ; The transmitting power of the UAV is , the user's transmission power is .

[0037] Assume the trajectory of the drone is , ground users The location is ,During the flight of the drone, the positions of all users remain unchanged.

[0038] Assume that the initial position of the drone is , without considering the acceleration and deceleration state of the drone, the movement of the drone is described as follows:

[0039]

[0040]

[0041] in, Indicates that the drone is Always The coordinates of the axes, Indicates that the drone is Always The coordinates of the axes; Indicates that the drone is Always The coordinates of the axes; Indicates that the drone is The flight speed at the moment, Indicates that the drone is The pitch angle at the moment, Indicates that the drone is Yaw angle at the moment.

[0042] In the present invention, it is assumed that the flight altitude of the UAV remains unchanged, that is, , thus, we get a two-dimensional model of the drone moving in the air:

[0043]

[0044] The present invention adopts the free space path loss model to describe the path loss of air-to-ground signals:

[0045] in, is the carrier frequency, is the speed of light, represents the path loss of air-to-ground signal; express The distance between the drone and the ground user at the moment:

[0046] Then, The drone and the The channel gain between users is:

[0047] in, is a random variable representing the small-scale fading coefficient of the communication channel.

[0048] S2, based on the channel gain between the drone and each user in each time slot, calculates the receiving power of each user; according to the initial resource allocation matrix (already assumed), calculates the signal power received by each user from the drone to other users, calculates the actual signal-to-noise ratio of the current user's receiving end according to the signal-to-noise ratio formula, and further calculates the rate obtained by each user.

[0049] In the n time slots, that is, time slots , the user's resource allocation scheme is used express, Indicates the subchannel indicator, in time slot , if The subchannels are assigned to the users, then ; If subchannels are not allocated to the users, then .

[0050] According to the channel model, the Users in time slot Use the The rate that can be obtained by a channel is shown in the following formula:

[0051] in, For the Users in time slot Use the The signal-to-noise ratio of a channel is calculated by the following formula:

[0052] in, For other users in the time slot Use the When the channel The interference generated by a user is calculated by the following formula:

[0053] Then, Users in time slot Use the The signal-to-noise ratio of a channel can be expressed as:

[0054] in, For the u The signal power received by each user from the drone to other users; For the receiving end ( uThe received power of each user).

[0055] S3, see Figure 4 Based on the channel gain between the drone and the user in each time slot, the rate at which each user uses each channel in each time slot is calculated; based on the rate at which each user uses each channel in each time slot, the proportional fair scheduling algorithm is used to determine the user priority corresponding to each channel and the number of video layers for each user in each channel; based on the user priority corresponding to each channel and the number of video layers for each user in each channel, users are assigned to each channel until the signal-to-noise ratio of all users in each channel meets the requirements.

[0056] Specifically, S2 can calculate the rate that each user can obtain when occupying a certain channel alone; select the corresponding number of video layers according to the sum of the rates of each user in all channels, for example, the user with the highest rate selects the maximum number of layers; starting from the first channel, divide the rate that the first user can obtain in the first channel by the balance coefficient to obtain the expected rate, divide the expected rate of each user in the first channel by the historical average rate, obtain the ratio of the expected rate to the historical average rate, and obtain the scheduling priority. Based on the user priority corresponding to each channel, assign users to each channel until the signal-to-noise ratio of all users in each channel meets the requirements. Select the user with the highest priority according to the priority, assign the first channel to the corresponding user, check and calculate whether the signal-to-noise ratio of all users using the channel meets the requirements, if not, cancel the assignment, find the user with the next priority, until all users are traversed, and then jump to the next channel, repeat the above process, when all users of all channels have completed the assignment, check whether the constraints are met, increase or decrease the number of selected video layers accordingly according to the satisfaction, and reallocate until the requirements are met.

[0057] The number of subcarriers available in each time slot channel is limited, that is, there is a situation where the video cannot be transmitted to the user with the highest quality. In this case, the proportional fair scheduling algorithm is used to build a resource allocation model, schedule users in each channel, and calculate the time slot. The rate of the user in the channel , and the user in front The average rate in a time slot , the scheduled priority formula is:

[0058] The user is in front t The average rate in a time slot is:

[0059] in, It is the selected time window, which represents how long the average rate includes the channel condition information in the past. When the user is frequently scheduled, its average rate will increase, the priority will decrease, and the probability of being scheduled will decrease; when the user is not scheduled for a long time, the average rate will decrease, the priority will increase, and the probability of being scheduled will increase.

[0060] Select users based on the rate at which drones are assigned to them For example, if the maximum rate is selected, the maximum number of layers is selected. For other rates, the corresponding number of layers is selected based on the ratio between the rate and the maximum rate. For example, if another rate is only half of the maximum rate, half the number of layers is selected.

[0061] After obtaining the user priority corresponding to each channel and the number of video layers of each user in each channel through the above method, users are allocated to each channel based on the user priority corresponding to each channel and the number of video layers of each user in each channel until the signal-to-noise ratio of all users in each channel meets the requirements, specifically: The drone is sent to the user The number of video layers is , the remaining number of layers is , is the total number of video layers.

[0062] Then the user The amount of data is , Indicates the amount of data in the base layer, Indicates The amount of data in the enhancement layer. The variance of the average rate of each user is calculated:

[0063] in, , represents the total average rate of all users; then the optimization objective function can be constructed based on this:

[0064] is the balance coefficient, and its value is and Therefore, the optimization problem is constructed as follows:

[0065] Among the above constraints, constraint 1 ensures that the signal-to-noise ratio received by the user is greater than the specified threshold value, constraints 2 and 3 indicate that the number of subchannels and bandwidth allocated to the user is lower than the total number of channels and total bandwidth, and constraint 4 indicates that the minimum number of video layers to be transmitted by a user cannot be less than 1 and the maximum number cannot exceed ,Constraint 5 indicates that the channel has only two states, allocated or unallocated.

[0066] The principle of the proportional fair scheduling algorithm of the present invention is: The proportional fair scheduling algorithm can take into account both system capacity and user fairness requirements, and achieve a good compromise in improving system capacity and user fairness. The algorithm can improve both system capacity and user fairness by proportionally scheduling resources in multiple consecutive time slots. The definition of proportional fair scheduling is as follows: Scheduling Mechanism is proportionally fair, it is feasible ( and ), if and for only if any other scheduling mechanism Satisfy the following formula:

[0067] in, is the set of all users, is the maximum capacity of the system, Is a user In the scheduling mechanism The average transmission rate under Is a user In the scheduling mechanism The average transmission rate under , researchers have proved that the definition of proportional fairness can also be expressed as the following optimization problem, and the optimal solution of this optimization problem is the proportional fairness vector ,in is the number of users.

[0068]

[0069] in, is a column matrix with elements equal to 1, When the average transmission rates of all users are equal, the objective function value in the optimization problem reaches the maximum, that is, the system is the fairest in this case.

[0070] definition For users In time slot The proportional fair utility function, whose value is equal to the current time slot The transmission rate of the internal users Before Average transmission rate in a time slot Ratio of:

[0071] Among them, the time slot Average transfer rate The expression is as follows:

[0072] As shown in the formula, the time slot The average transfer rate It is through the The average transmission rate of the time slot is obtained iteratively. Figure 3 Given Iterative process of calculation.

[0073] Considering that there is no average transmission rate of the user in the first time slot, the average transmission rate of the user in the first time slot is equal to its transmission rate, which is expressed as follows:

[0074] According to the existing proof, the formula can be further transformed into:

[0075] Due to the time window It is known that the formula can be further expressed as the sum of the proportional fairness functions of all users as follows:

[0076] As can be seen from the formula, the proportional fair scheduling algorithm will give priority to the and lower average transfer rates Users Allocate resources to achieve the goal of balancing system capacity and user fairness.

[0077] An embodiment of the present invention provides a bit rate selection and time-frequency resource allocation system for unmanned aerial vehicle video streaming, including: The location determination module obtains the location information of the drone and the user and determines the distance between the drone and the user; The channel gain calculation module calculates the channel gain between the drone and the user in each time slot based on the distance between the drone and the user and the location information of the drone and the user; The priority scheduling module calculates the rate at which each user uses each channel in each time slot based on the channel gain between the drone and the user in each time slot. Based on the rate at which each user uses each channel in each time slot, the proportional fair scheduling algorithm is used to determine the user priority corresponding to each channel and the number of video layers for each user in each channel. The resource allocation module allocates users to each channel based on the user priority corresponding to each channel and the number of video layers of each user in each channel until the signal-to-noise ratio of all users in each channel meets the requirements.

[0078] In another embodiment of the present invention, the present invention also provides a storage medium, specifically a computer-readable storage medium (Memory), which is a memory device in a terminal device for storing programs and data. It is understandable that the computer-readable storage medium here can include both the built-in storage medium in the terminal device and the extended storage medium supported by the terminal device, and can be any tangible medium containing or storing a program, which can be used by an instruction execution system, device or device or used in combination with it. The computer-readable storage medium provides a storage space, which stores the operating system of the terminal. In addition, one or more instructions suitable for being loaded and executed by the processor are also stored in the storage space, and these instructions can be one or more computer programs (including program codes). It should be noted that more specific examples (non-exhaustive list) of the computer-readable storage medium here include: an electrical connection with one or more wires, a portable disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above.

[0079] Computer readable storage media also include data signals propagated in baseband or as part of a carrier wave, which carry readable program codes. Such propagated data signals can take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. The readable storage medium can also be any readable medium other than a readable storage medium, which can send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, device, or device. The program code contained on the readable storage medium can be transmitted using any appropriate medium, including but not limited to wireless, wired, optical cable, RF, etc., or any suitable combination of the above.

[0080] Program code for performing the operations of the present invention may be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java, C++, etc., and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user computing device, partially on the user device, as a separate software package, partially on the user computing device and partially on a remote computing device, or entirely on a remote computing device or server. In the case of a remote computing device, the remote computing device may be connected to the user computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computing device (e.g., through the Internet using an Internet service provider).

[0081] The processor may load and execute one or more instructions stored in a computer-readable storage medium to implement the corresponding steps of the method for selecting bit rate and allocating time-frequency resources for drone video streaming in the above-mentioned embodiment.

[0082] The above are only preferred embodiments of the present invention and are not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for bit rate selection and time-frequency resource allocation for drone video streaming, characterized in that: The following steps are involved: S1, obtain the location information of the drone and the user, and determine the distance between the drone and the user; S2, based on the distance between the drone and the user and the location information of the drone and the user, calculate the channel gain between the drone and the user in each time slot; S3, based on the channel gain between the drone and the user in each time slot, calculates the rate at which each user uses each channel in each time slot; Based on the rate at which each user uses each channel in each time slot, a proportional fair scheduling algorithm is used to determine the user priority corresponding to each channel and the number of video layers for each user in each channel; S4, based on the user priority corresponding to each channel and the number of video layers of each user in each channel, assign users to each channel until the signal-to-noise ratio of all users in each channel meets the requirements.

2. The method for bit rate selection and time-frequency resource allocation for drone video streaming according to claim 1 is characterized in that: The distance between the drone and the user is described as: in, For drones Always The coordinates of the axes; Indicates that the drone is Always The coordinates of the axes; Indicates that the drone is Always The coordinates of the axis.

3. The method for bit rate selection and time-frequency resource allocation for drone video streaming according to claim 1 is characterized in that: The channel gain between the drone and the user in each time slot is: in, is a random variable, representing the small-scale fading coefficient of the communication channel; is the path loss from the drone to the user signal: in, is the carrier frequency; is the speed of light; express The distance between the drone and the user at any given moment.

4. The method for selecting bit rate and allocating time-frequency resources for streaming drone video according to claim 1, characterized in that: The rate at which each user uses each channel in each time slot is: in, For time slot t Next u Users use m The rate of the channels; B For the m The bandwidth of the channel; M is the total number of channels; For the Users in time slot Use the The signal-to-noise ratio of a channel.

5. The method for bit rate selection and time-frequency resource allocation for drone video streaming according to claim 1, characterized in that: Based on the rate at which each user uses each channel in each time slot, a proportional fair scheduling algorithm is used to determine the user priority corresponding to each channel and the number of video layers for each user in each channel, specifically: According to the rate at which each user uses each channel in each time slot, the sum of the rates of each user in all channels in each time slot is obtained; Based on the sum of the rates of each user in all channels in each time slot, select the number of video layers for each user in each channel; Based on the rate at which each user uses each channel in each time slot, a proportional fair scheduling algorithm is used to find the user priority corresponding to each channel.

6. The method for bit rate selection and time-frequency resource allocation for drone video streaming according to claim 1, characterized in that: The specific method of allocating users to each channel is as follows: in, is the balance coefficient; is the variance of the average rate of each user and the total average rate of all users; For the Number of video layers per user; L is the total number of video layers.

7. The method for bit rate selection and time-frequency resource allocation for drone video streaming according to claim 6, characterized in that: Said in, , represents the total average rate of all users; U is the total number of users; For the u Users in front t The average rate within a time slot.

8. The method for bit rate selection and time-frequency resource allocation for drone video streaming according to claim 1, characterized in that: The signal-to-noise ratio of all users of each channel meets the requirements, specifically: in, For the u The signal power received by each user from the drone to other users; For the time slot Neidi The subchannels are assigned to the Channel indicators for each user; for t Drones and the Channel gain between users; For the i The received power of each user.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method for selecting bit rate and allocating time-frequency resources for streaming drone video according to any one of claims 1 to 8 is implemented.

10. A bit rate selection and time-frequency resource allocation system for drone video streaming, characterized in that: include: The location determination module obtains the location information of the drone and the user and determines the distance between the drone and the user; The channel gain calculation module calculates the channel gain between the drone and the user in each time slot based on the distance between the drone and the user and the location information of the drone and the user; The priority scheduling module calculates the rate at which each user uses each channel in each time slot based on the channel gain between the drone and the user in each time slot; Based on the rate at which each user uses each channel in each time slot, a proportional fair scheduling algorithm is used to determine the user priority corresponding to each channel and the number of video layers for each user in each channel; The resource allocation module allocates users to each channel based on the user priority corresponding to each channel and the number of video layers of each user in each channel until the signal-to-noise ratio of all users in each channel meets the requirements.

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