A method and system for selecting a video stream bit rate and allocating time-frequency resources for a drone

Abstract

The application discloses a kind of unmanned aerial vehicle video stream transmission code rate selection and time-frequency resource allocation method and system, method is first by obtaining the position information of unmanned aerial vehicle and user to determine the distance between them. Then, based on these position information and distance, the channel gain between unmanned aerial vehicle and user under each time slot is calculated. Then, the rate of each user using each channel under each time slot is calculated using these channel gains. On this basis, the proportional fair scheduling algorithm is used to determine the user priority corresponding to each channel and the video layer number of each user in each channel. Finally, according to these priorities and video layer numbers, user allocation is performed for each channel until the signal-to-noise ratio of all users of each channel meets the requirements. The method aims to optimize the transmission efficiency and quality of unmanned aerial vehicle video stream and improve user experience.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of unmanned aerial vehicle wireless video stream backhaul, and relates to a method and system for selecting a video stream code rate of an unmanned aerial vehicle and allocating time-frequency resources. BACKGROUND

[0002] With the rapid development of unmanned aerial vehicle technology, the one-to-many communication field of unmanned aerial vehicles, i.e., one machine multi-control technology, has shown great potential and value in practical applications. This technology allows a single unmanned aerial vehicle to be cooperatively controlled by multiple users, thereby realizing a more efficient and flexible operation mode. Existing high-end unmanned aerial vehicles have adopted multi-user control technology, enabling team members such as pilots, camera operators, and directors to jointly operate a single unmanned aerial vehicle, greatly improving the efficiency of film production and industrial detection.

[0003] In these advanced unmanned aerial vehicle 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 multiple users to monitor and navigate in real time at the same time, and ensure the real-time, stability, and reliability of data transmission. However, the communication environment of unmanned aerial vehicles is relatively complex, and the spectrum resources are limited, which makes the allocation of bandwidth resources a key issue.

[0004] In practical applications, unmanned aerial vehicle communication will be disturbed by various factors such as terrain, ground cover, and noise generated by natural and human activities, resulting in a decline or even interruption of communication quality. To solve this problem, researchers usually use dynamic resource allocation algorithms such as machine learning to optimize the allocation of bandwidth resources by tracking the fluctuations in network conditions in real time. This dynamic allocation method can adjust the use of time-frequency resources in real time according to the needs of users and the state of the system, thereby improving resource utilization and anti-interference capability.

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

[0006] However, despite the remarkable achievements of SVC technology and dynamic resource allocation algorithms in unmanned aerial vehicle communication, there are still some problems to be solved. For example, the static resource allocation method is simple and direct, but the resource utilization rate is low and the anti-interference capability is weak; while the dynamic resource allocation method can improve resource utilization, but requires more complex scheduling algorithms and signaling interaction, and may face the problem of poor user fairness in practical applications. SUMMARY

[0007] The present application aims at solving the technical problems of weak anti-interference ability of static resource allocation of SVC technology and dynamic resource allocation algorithm, high complexity of dynamic resource allocation scheduling algorithm and poor user fairness in the unmanned aerial vehicle communication system, and provides a method and system for unmanned aerial vehicle video stream code rate selection and time-frequency resource allocation.

[0008] To achieve the above-mentioned purpose, the present application adopts the following technical solutions:

[0009] The present application provides a method for unmanned aerial vehicle video stream code rate selection and time-frequency resource allocation in the first aspect, comprising the following steps:

[0010] S1, obtaining the position information of the unmanned aerial vehicle and the user, and determining the distance between the unmanned aerial vehicle and the user;

[0011] S2, calculating the channel gain between the unmanned aerial vehicle and the user in each time slot based on the distance between the unmanned aerial vehicle and the user and the position information of the unmanned aerial vehicle and the user;

[0012] S3, calculating the rate of each user using each channel in each time slot based on the channel gain between the unmanned aerial vehicle and the user in each time slot, and determining the user priority corresponding to each channel and the video layer number of each user in each channel based on the rate of each user using each channel in each time slot by using the proportional fair scheduling algorithm;

[0013] S4, allocating users to each channel based on the user priority corresponding to each channel and the video layer number of each user in each channel until the signal-to-noise ratio of all users of each channel meets the requirements.

[0014] Further, the distance between the unmanned aerial vehicle and the user is described as:

[0015]

[0016] wherein, is the coordinate of the unmanned aerial vehicle in the axis at the moment is the coordinate of the unmanned aerial vehicle in the axis at the moment is the coordinate of the unmanned aerial vehicle in the axis at the moment is the coordinate of the unmanned aerial vehicle in the axis at the moment is the coordinate of the unmanned aerial vehicle in the axis at the moment is the coordinate of the unmanned aerial vehicle in the axis at the moment is the coordinate of the unmanned aerial vehicle in the axis at the moment is the coordinate of the unmanned aerial vehicle in the axis at the moment

[0017] Further, the channel gain between the unmanned aerial vehicle and the user in each time slot is:

[0018]

[0019] wherein,​ For random variables, representing the small-scale fading coefficient of the communication channel; For the path loss of the signal from the drone to the user:

[0020] in, For carrier frequency; The speed of light; express The distance between the drone and the user at all times.

[0021] Furthermore, the rate at which each user uses each channel in each time slot is:

[0022]

[0023] in, For time slots t Next u The user used the number m The rate of each channel; B For the first m The bandwidth of each channel; M Total number of channels; For the first Individual users in time slots Internal use of the first Signal-to-noise ratio of each channel.

[0024] 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 for each channel and the number of video layers for each user on each channel, specifically:

[0025] Based on the rate at which each user uses each channel in each time slot, the sum of the rates of each user across all channels in each time slot is obtained;

[0026] The number of video layers for each user in each channel is selected based on the sum of the rates of each user across all channels in each time slot;

[0027] 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.

[0028] Furthermore, the specific process of allocating users to each channel is as follows:

[0029]

[0030] in, This is the balance coefficient; The variance of the average rate for each user to the total average rate for all users; For the first the number of video layers of the user; L the total number of video layers.

[0031] Further, the

[0032]

[0033] wherein, represents the average rate of all users in total; U is the total number of users; is the average rate of the u th user in the previous t time slots.

[0034] Further, the signal-to-noise ratio of all users of each channel meets the requirement, specifically:

[0035]

[0036] wherein, is the signal power received by the u th user from the unmanned aerial vehicle to other users; is the channel indicator of the th sub-channel allocated to the th user in the time slot is the channel gain between the unmanned aerial vehicle and the t th user in the time slot is the received power of the i th user.

[0037] The second aspect of the present application provides a computer readable storage medium, which stores a computer program, and the computer program is executed by a processor to realize the above-mentioned unmanned aerial vehicle video streaming code rate selection and time-frequency resource allocation method.

[0038] The third aspect of the present application provides an unmanned aerial vehicle video streaming code rate selection and time-frequency resource allocation system, comprising:

[0039] A position determination module acquires the position information of the unmanned aerial vehicle and the user, and determines the distance between the unmanned aerial vehicle and the user.

[0040] A channel gain calculation module calculates the channel gain between the unmanned aerial vehicle and the user in each time slot based on the distance between the unmanned aerial vehicle and the user and the position information of the unmanned aerial vehicle and the user.

[0041] ​​The priority scheduling module calculates the rate of each user using each channel under each time slot based on the channel gain between the unmanned aerial vehicle and the user under each time slot; the proportional fair scheduling algorithm is adopted to determine the user priority corresponding to each channel and the video layer number of each user on each channel based on the rate of each user using each channel under each time slot;

[0042] The resource allocation module allocates users to each channel based on the user priority corresponding to each channel and the video layer number of each user on each channel until the signal-to-noise ratio of all users of each channel meets the requirement.

[0043] Compared with the prior art, the present application has the following beneficial effects:

[0044] The present application discloses a kind of unmanned aerial vehicle video stream's code rate selection and time-frequency resource allocation method, by real-time acquisition unmanned aerial vehicle and the position information of user, and determine the distance between unmanned aerial vehicle and user according to this, the present application can dynamically adjust transmission strategy, ensure the stable transmission of video stream under different distances.Based on the calculation of channel gain, the present application can accurately evaluate the communication quality between unmanned aerial vehicle and user under each time slot, so as to optimize code rate selection and resource allocation, effectively reduce the error rate in transmission, improve the definition and fluency of video stream.The present application adopts proportional fair scheduling algorithm, according to the rate of each user using each channel under each time slot, dynamically adjust user priority and video layer number, ensure the fairness and efficiency of resource allocation.Can according to the actual demand of different users and network condition, transmission strategy is flexibly adjusted, effectively deal with complex and changeable communication environment, improve the overall performance of system.Through the fine management of allocating user to each channel, the present application ensures that the signal-to-noise ratio of all users of each channel meets the requirement, avoids the waste and conflict of resources.The method can make full use of limited time-frequency resources, realize the optimal allocation of resources, improve the throughput and spectral efficiency of system.The method can also dynamically adjust video layer number and code rate according to the actual demand of user and network condition, meet the different needs of user to video quality.

[0045] Further, by calculating the sum of the rates of each user on all channels in each time slot, data support is provided for the selection of the video layer number. This refined calculation method ensures the rationality and efficiency of resource allocation, so that each user can obtain the most suitable video layer number according to their own transmission needs and channel conditions, thereby maximizing the utilization of resources while ensuring video quality. Using the proportional fair scheduling algorithm, the user priority is dynamically adjusted according to the rate of each user using each channel in each time slot. This strategy not only considers the instantaneous transmission rate of the user, but also takes into account the long-term fairness. It ensures that all users can obtain a relatively fair resource allocation opportunity, avoiding unfair resource allocation due to 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 video layer number accordingly, the system can quickly adapt to changes in the network environment. Whether it is fluctuations in channel quality or changes in user demand, the system can respond through flexible scheduling strategies, thereby enhancing the adaptability and robustness of the system. BRIEF DESCRIPTION OF DRAWINGS

[0046] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following will briefly introduce the drawings needed to be used in the embodiments. It should be understood that the following drawings only show some embodiments of the present application, and therefore should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can also be obtained without creative labor.

[0047] Figure 1 For the UAV video backhaul scene diagram in the embodiments of the present application;

[0048] Figure 2 For the flowchart of the UAV video stream code rate selection and time-frequency resource allocation method in the embodiments of the present application;

[0049] Figure 3 For the iteration process diagram of the average transmission rate calculation of the time slot t

[0050] Figure 4 For the flowchart of the proportional fair scheduling algorithm. DETAILED DESCRIPTION

[0051] In order to make the purpose, technical solutions and advantages of the embodiments of the present application more clear, the following will combine the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all. The components of the embodiments of the present application described and indicated in the drawings here can be arranged and designed in various different configurations.

[0052] ​Therefore, the following detailed description of the embodiments of the application provided in the accompanying drawings is not intended to limit the scope of the application claimed, but merely represents selected embodiments of the application. All other embodiments obtained by those of ordinary skill in the art based on the embodiments in the application without creative labor fall within the scope of the application.

[0053] It should be noted that similar reference numbers and letters represent similar items in the following drawings, and therefore, once an item is defined in one drawing, it need not be further defined and explained in subsequent drawings.

[0054] In the description of the embodiments of the application, it should be noted that if the terms "upper", "lower", "horizontal", "inner", etc. indicate the orientation or positional relationship based on the orientation or positional relationship shown in the drawings, or the orientation or positional relationship when the product of the application is usually placed, and are only for the convenience of describing the application and simplifying the description, and therefore cannot be understood as indicating or implying that the device or element must have a particular orientation, be constructed and operated in a particular orientation, and therefore cannot be understood as limiting the application. In addition, the terms "first", "second", etc. are only used to distinguish the description and cannot be understood as indicating or implying relative importance.

[0055] In addition, if the term "horizontal" appears, it does not mean that the component must be absolutely horizontal, but can be slightly inclined. For example, "horizontal" only means that its direction is relatively more horizontal than "vertical", and does not mean that the structure must be completely horizontal, but can be slightly inclined.

[0056] In the description of the embodiments of the application, it should also be noted that unless otherwise explicitly specified and limited, if the terms "arrangement", "installation", "connection", "connection" appear, they should be understood in a broad sense, for example, they can be fixedly connected, or can be detachably connected, or integrally connected; can be mechanically connected, or can be electrically connected; can be directly connected, or can be indirectly connected through an intermediate medium; can be the communication between the two elements inside. For those of ordinary skill in the art, the specific meaning of the above terms in the application can be understood according to the specific circumstances.

[0057] The application will be described in further detail below in conjunction with the accompanying drawings:

[0058] The application discloses a method for selecting a video stream code rate of a UAV and allocating time-frequency resources, comprising the following steps:

[0059] S1, obtaining the position information of the UAV and the user, and determining the distance between the UAV and the user; based on the distance between the UAV and the user and the position information of the UAV and the user, calculating the channel gain between the UAV and each user in each time slot;

[0060] Referring toFigure 1 When the UAV video is streaming back, the video captured by the UAV during flight is transmitted to each user, and the number of video transmission layers is selected for the user according to the channel condition of the user and the demand of the user for video quality, to ensure the real-time transmission. The UAV is controlled by one of the users.

[0061] In a scenario of one UAV and multiple users, the user set is denoted as The UAV and the users are both equipped with omnidirectional antennas, and the time slots are divided into time slots, denoted as the set The total frequency band of all users is divided into sub-channels, denoted as the set Each sub-band has a bandwidth of ; the transmission power of the UAV is , and the transmission power of the user is .

[0062] Let the trajectory of the UAV be , and the position of the ground user be During the flight of the UAV, the positions of all users remain unchanged.

[0063] Assuming that the initial position of the UAV is , and without considering the acceleration and deceleration state of the UAV, the movement of the UAV is described as follows:

[0064]

[0065]

[0066]

[0067] wherein represents the coordinate of the UAV on the axis at the moment, represents the coordinate of the UAV on the axis at the moment; represents the coordinate of the UAV on the axis at the moment; represents the flight speed of the UAV at the moment, represents the pitch angle of the UAV at the moment, represents the yaw angle of the UAV at the moment.

[0068] In the present application, it is assumed that the flight height of the UAV remains unchanged, i.e. Thus, a two-dimensional model of the drone's movement in the air is obtained:

[0069]

[0070]

[0071] This invention uses a free-space path loss model to describe the path loss of air-to-ground signals:

[0072]

[0073] in, For carrier frequency, At the speed of light, This represents the path loss of air-to-ground signals; express The distance between the drone and the ground user at any time:

[0074]

[0075] Then, the first The drone and the first time slot The channel gain between users is:

[0076]

[0077] in, is a random variable representing the small-scale fading coefficient of the communication channel.

[0078] S2, based on the channel gain between the UAV and each user in each time slot, calculate the received power of each user; according to the initial resource allocation matrix (already assumed), calculate the signal power received by each user from the UAV sent to other users, calculate the actual signal-to-noise ratio of the current user's receiver according to the signal-to-noise ratio formula, and further calculate the rate obtained by each user.

[0079] In the n In a time slot, i.e. User resource allocation scheme express, Indicates the sub-channel indicator, in the time slot If the first The first sub-channel was assigned to the second... For each user, If the first The first subchannel was not assigned to the first For each user, .

[0080] Based on the channel model, the first... Individual users in time slots Internal use of the first The achievable rate for each channel is shown in the following formula:

[0081]

[0082] in, For the first Individual users in time slots Internal use of the first The signal-to-noise ratio of each channel is calculated by the following formula:

[0083]

[0084] in, For other users in time slots Internal use of the first When the channel is , for the The interference generated by a single user is calculated using the following formula:

[0085]

[0086] Then, the first Individual users in time slots Internal use of the first The signal-to-noise ratio of each channel can be expressed as:

[0087]

[0088] in, For the first u The signal power received by a user from a drone transmitted to other users; For the receiving end (the first) u The received power of (each user).

[0089] S3, see S3. Figure 4 Based on the channel gain between the UAV 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, 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. 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.

[0090] Specifically, S2 can calculate the rate each user can obtain when occupying a channel alone; the corresponding video layer number is selected according to the sum of the rates of each user on all channels, for example, the user with the maximum rate selects the maximum layer number; starting from the first channel, the rate each user can obtain in the first channel is divided by the balance coefficient to obtain the expected rate, the expected rate of each user in the first channel is divided by the historical average rate to obtain the ratio of the expected rate to the historical average rate, the scheduling priority is obtained, users are allocated to each channel based on the priority of the corresponding user of each channel, until the signal-to-noise ratio of all users of each channel meets the requirement. The user with the maximum priority is selected according to the priority, the first channel is allocated to the corresponding user, and it is checked whether the signal-to-noise ratio of all users using the channel meets the requirement, if not, the allocation is revoked, the next priority user is found, and the above process is repeated until all users are traversed, and then the next channel is jumped to, and the above process is repeated. When all users of all channels are allocated, it is checked whether the constraint is met, and the selected video layer number is increased or decreased accordingly according to the meeting condition, and then re-allocated until the requirement is met.

[0091] The number of subcarriers available for each time slot channel is limited, that is, there are cases where the video cannot be transmitted to the user at the highest quality. In this case, the proportional fair scheduling algorithm is used to construct a resource allocation model, and users are scheduled in each channel to calculate the rate of the user in the channel , and the average rate of the user in the previous time slot The priority formula for scheduling is:

[0092]

[0093] The average rate of the user in the previous t time slot is:

[0094]

[0095] wherein, is the selected time window, representing how long the channel condition information contained in the average rate. When the user is frequently scheduled, the average rate will increase, the priority will decrease, and the probability of being scheduled will decrease; when the user has not been scheduled for a long time, the average rate will decrease, the priority will increase, and the probability of being scheduled will increase.

[0096] The video layer number of the user is selected according to the rate allocated to the user by the unmanned aerial vehicle, for example, the maximum layer number is selected for the maximum rate, and other rates are selected according to the ratio of the rate to the maximum rate to select the corresponding layer number, for example, the layer number of a certain rate is selected as half of the maximum layer number when the rate is only half of the maximum rate.

[0097] ​After obtaining the user priority for each channel and the number of video layers for each user in each channel using the above method, users are assigned to each channel based on the user priority and the number of video layers for each user in each channel, until the signal-to-noise ratio of all users in each channel meets the requirements. Specifically:

[0098] Drones sent to users The number of video layers is The remaining number of floors is , This represents the total number of video layers.

[0099] Then the user The amount of data is , This indicates the amount of data in the base layer. Indicates the first The amount of data for each enhancement layer. The variance of the average rate for each user is calculated:

[0100]

[0101] in, Let represent the total average rate of all users; then, the optimization objective function can be constructed based on this:

[0102]

[0103] The balance coefficient takes a value of 100%. and Therefore, the optimization problem is as follows:

[0104]

[0105] Of the constraints mentioned above, constraint 1 ensures that the signal-to-noise ratio received by the user is greater than a specified threshold; constraints 2 and 3 indicate that the number of sub-channels and bandwidth allocated to the user are lower than the total number of channels and total bandwidth; and constraint 4 indicates that the minimum number of video layers a user needs to transmit cannot be less than 1, and the maximum cannot exceed 1. Constraint 5 indicates that the channel has only two states: allocated or unallocated.

[0106] The principle of the proportional fair scheduling algorithm of this invention is as follows:

[0107] The proportional fair scheduling algorithm balances system capacity and user fairness requirements, achieving a good trade-off between improving both. This algorithm improves both system capacity and user fairness simultaneously by proportionally and fairly scheduling resources across multiple consecutive time slots. The definition of proportional fair scheduling is as follows:

[0108] A scheduling mechanism It is proportionally fair, and it is feasible. and ), if and only if any other scheduling mechanism Satisfy the following formula:

[0109]

[0110] in, It is a collection of all users. That is the system's maximum capacity. User In scheduling mechanism The average transmission rate under these conditions, while User In scheduling mechanism The average transmission rate under the given conditions. Let Currently, some researchers have proven that the definition of proportional fairness can also be expressed as the following optimization problem, and the optimal solution to this optimization problem is the proportional fairness vector. ,in It represents the number of users.

[0111]

[0112] in, It is a column matrix with elements equal to 1. When all users have the same average transmission rate, the objective function in the optimization problem reaches its maximum value, meaning the system is most equitable under these conditions.

[0113] definition For users In the time slot The proportional fairness utility function, whose value is equal to the current time slot. Internal user transmission rate Compared to before Average transmission rate within a time slot The ratio:

[0114]

[0115] Among them, time slot Internal average transmission rate The expression is as follows:

[0116]

[0117] As shown in the formula, time slot average transmission rate Through the front The average transmission rate of the time slot is obtained through iteration. Figure 3 Given The iterative process of calculation.

[0118] Considering that there is no average transmission rate for any user in the first time slot, we set the average transmission rate of a user in the first time slot to be equal to its transmission rate, as follows:

[0119]

[0120] Based on the existing proof, the formula can be further transformed into:

[0121]

[0122] Due to the time window As is known, the formula can be further expressed as the sum of proportional fairness functions for all users as follows:

[0123]

[0124] As can be seen from the formula, the proportional fair scheduling algorithm prioritizes scheduling data with higher transmission rates. and lower average transmission rate users Resources are allocated to achieve the goal of balancing system capacity and user fairness.

[0125] One embodiment of the present invention provides a bitrate selection and time-frequency resource allocation system for drone video streaming, comprising:

[0126] The location determination module acquires the location information of the drone and the user, and determines the distance between the drone and the user;

[0127] The channel gain calculation module calculates the channel gain between the UAV and the user in each time slot based on the distance between the UAV and the user and the location information of the UAV and the user.

[0128] 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 UAV and the user in each time slot; based on the rate at which each user uses each channel in each time slot, it uses a 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.

[0129] The resource allocation module allocates users to each channel based on the user priority corresponding to each channel and the number of video layers for each user on each channel, until the signal-to-noise ratio of all users on each channel meets the requirements.

[0130] In still another embodiment of the present application, a storage medium, specifically a computer readable storage medium (Memory) is also provided. The computer readable storage medium is a memory device in the terminal equipment, for storing programs and data. It can be understood that the computer readable storage medium herein can include the built-in storage medium in the terminal equipment, and of course can also include the expansion storage medium supported by the terminal equipment, and can be any tangible medium containing or storing programs, which can be used by or in combination with the instruction execution system, device or apparatus. The computer readable storage medium provides a storage space, which stores the operating system of the terminal. Moreover, one or more instructions suitable for being loaded and executed by the processor are also stored in the storage space, which 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 herein include: an electrical connection with one or more conductive 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.

[0131] The computer readable storage medium also includes a data signal carrying the readable program code in a baseband or as a part of a carrier, where the readable program code is carried by the data signal. Such a propagated data signal can take any of a variety of forms, including but not limited to electro-magnetic, optical, or any suitable combination thereof. The readable storage medium can also be any readable medium that can be used to carry the readable program code in any suitable manner, where the readable program code can be executed by or in combination with an instruction execution system, device or apparatus. The readable program code contained in the readable storage medium can be transmitted in any suitable manner, including but not limited to wireless, wired, optical, RF, or any suitable combination thereof.

[0132] The program code for carrying out operations of the present application can be written in any combination of one or more programming languages, including an object oriented programming language such as Java, C++, or the like, and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code can execute entirely on the user's computing device, partly on the user's computing device, as a stand-alone software package, partly on the user's computing device and partly on a remote computing device or entirely on the remote computing device or server. In the latter scenario, the remote computing device can be connected to the user's computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection can be made to an external computing device, such as through the Internet using an Internet Service Provider.

[0133] The one or more instructions stored in the computer readable storage medium can be loaded and executed by the processor to implement the corresponding steps of the method for selecting a video stream transmission rate and allocating time-frequency resources of a UAV in the above embodiments.

[0134] The above merely shows the preferred embodiments of the present application, but should not be used to limit the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the protection scope of the present application.

Claims

1. A method for bitrate selection and time-frequency resource allocation in UAV video stream transmission, characterized in that, Includes the following steps: S1, acquire 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 UAV 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, a proportional fair scheduling algorithm is used to determine the user priority for each channel and the number of video layers for each user on each channel, specifically: Based on the rate at which each user uses each channel in each time slot, the sum of the rates of each user across all channels in each time slot is obtained; The number of video layers for each user in each channel is selected based on the sum of the rates of each user across all channels 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 find the user priority corresponding to 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. The process of allocating users to each channel specifically involves constructing an optimization objective function: in, This is the balance coefficient; The variance of the average rate for each user to the total average rate for all users; For the first The number of video layers per user; L This represents the total number of video layers. U This represents the total number of users. The signal-to-noise ratio (SNR) of all users in each channel meets the requirements, specifically: in, For the first u The signal power received by a user from a drone transmitted to other users; In time slot Inner The first sub-channel was assigned to the second... Channel indicator for each user; for t UAVs and the first Channel gain between users; For the first i Received power of individual users ； express No. u The user in the first Height The signal-to-noise ratio of the channel; Represents a set of time slots; Represents a set of users; This represents the set of sub-channels.

2. The method for bitrate selection and time-frequency resource allocation in UAV video stream transmission according to claim 1, characterized in that, The distance between the drone and the user is described as follows: in, For drones Always The coordinates of the axis; Indicates that drones are in Always The coordinates of the axis; Indicates that drones are in Always The coordinates of the axis; This represents the user's x-coordinate at time t; Indicates that the user is Always The coordinates of the axis; Indicates that the user is Always The coordinates of the axis.

3. The method for bitrate selection and time-frequency resource allocation in UAV video stream transmission according to claim 1, characterized in that, The channel gain between the UAV and the user in each time slot is: in, For random variables, representing the small-scale fading coefficient of the communication channel; Path loss of signal from drone to user: in, For carrier frequency; The speed of light; express The distance between the drone and the user at all times.

4. The method for bitrate selection and time-frequency resource allocation in UAV video stream transmission according to claim 1, characterized in that, The rate at which each user uses each channel in each time slot is: in, For time slots t Next u The user used the number m The rate of each channel; B For the first m The bandwidth of each channel; M Total number of channels; For the first Individual users in time slots Internal use of the first Signal-to-noise ratio of each channel.

5. The method for bitrate selection and time-frequency resource allocation for UAV video stream transmission according to claim 1, characterized in that, The in, , representing the total average rate of all users; U This represents the total number of users. For the first u One user in front t The average rate within each time slot.

6. 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 bitrate selection and time-frequency resource allocation method for UAV video stream transmission according to any one of claims 1-5.

7. A bitrate selection and time-frequency resource allocation system for UAV video stream transmission, based on the bitrate selection and time-frequency resource allocation method for UAV video stream transmission as described in claim 1, characterized in that, include: The location determination module acquires 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 UAV and the user in each time slot based on the distance between the UAV and the user and the location information of the UAV 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 UAV 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 for 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 for each user on each channel, until the signal-to-noise ratio of all users on each channel meets the requirements.

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