A method and system for air-ground collaborative communication service based on machine learning
A communication service, air-ground coordination technology, applied in control/regulation systems, instruments, 3D position/channel control, etc., can solve the problems of low service quality and low efficiency, and achieve high robustness, strong environmental adaptability, The effect of adapting to changes in the number of ground users
Active Publication Date: 2022-06-21
HARBIN INST OF TECH
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[0004] In view of the above problems, the present invention proposes a machine learning-based air-ground collaborative communication service method and system to solve the problem of low service quality and low efficiency in the prior art that only rely on drones to provide communication services
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[0066] In order for those skilled in the art to better understand the solutions of the present invention, the exemplary embodiments or embodiments of the present invention will be described below with reference to the accompanying drawings. Obviously, the described implementations or examples are only some implementations or examples of the present invention, but not all of them. All other implementations or examples obtained by those of ordinary skill in the art without creative work based on the implementations or examples of the present invention shall fall within the protection scope of the present invention.
[0067] In order to solve the communication service problem of ground users, the present invention proposes an air-ground cooperative communication service method based on machine learning, and trains the cooperative communication service strategy of drones and unmanned vehicles through the deep reinforcement learning method, so as to provide effective and efficient c...
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A machine learning-based air-ground collaborative communication service method and system, which relate to the technical field of air-ground collaborative communication services, and are used to solve the problems of poor service quality and low efficiency in the prior art that only rely on unmanned aerial vehicles to provide communication services. The technical points of the present invention include: obtaining the environmental information of each UAV and unmanned vehicle in the communication service; inputting the environmental information into the pre-trained deep neural network model, and obtaining the coordination of UAV and unmanned vehicle Communication Services Policy Directive. The invention can solve the problem of mutual communication between ground users and the outside world or between ground users after the ground communication base station is damaged, and can solve the problem of insufficient availability of mobile communication equipment. The invention can provide high-quality and fair communication services for ground users , has high robustness and strong environmental adaptability, and can be applied to air-ground collaborative communication services.
Description
technical field [0001] The invention relates to the technical field of air-ground cooperative communication services, in particular to a method and system for air-ground cooperative communication services based on machine learning. Background technique [0002] There are two main ways for drones to provide communication services for ground users. The first way is to use the drone as a relay point for communication; in this mode of use, the drone is responsible for forwarding the communication between the user and the base station. Communication messages to provide communication services to users. In this communication service mode, how to optimize the location layout of UAVs and how to allocate communication channels to different users need to be solved. The usual practice is to model the above problem as a multi-objective optimization problem, and use the convex optimization method or intelligent algorithm to solve it, and obtain the position distribution of the UAV and th...
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IPC IPC(8): G05D1/10
CPCG05D1/101
Inventor 白成超郭继峰颜鹏郑红星
Owner HARBIN INST OF TECH