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Multi-unmanned aerial vehicle and user cooperative communication optimization method based on MAPPO algorithm

A multi-UAV, optimization method technology, applied in general control systems, instruments, adaptive control, etc., to achieve the effect of reasonable design and simple steps

Active Publication Date: 2021-09-07
中国人民解放军火箭军工程大学
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AI Technical Summary

Problems solved by technology

The optimization target is limited to UAV or ground access control, and has not been researched from multiple UAVs and multiple user levels

Method used

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  • Multi-unmanned aerial vehicle and user cooperative communication optimization method based on MAPPO algorithm

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Embodiment Construction

[0090] Such as figure 1 Shown is a multi-unmanned aerial vehicle and user collaborative communication optimization method based on the MAPPO algorithm, comprising the following steps:

[0091] Step 1. Establishment of UAV network model and user network model:

[0092] Step 101, set the parameter of the UAV Actor network to φ, and the parameter of the UAV Critic network to ω 1 , the parameter of the user Actor network is θ, and the parameter of the user Critic network is ω 2 ;

[0093] Step 102, setting the initial value of the parameter φ of the UAV Actor network to φ(0), and the parameter ω of the UAV Critic network 1 The initial value of ω 1 (0), the initial value of the parameter θ of the user Actor network is θ(0), and the parameter ω of the user Critic network 2 The initial value of ω 2 (0); where, φ(0), ω 1 (0), θ(0), and ω 2 (0) Satisfy the orthogonal initialization of the neural network;

[0094] Step 2, UAV and user scene setting:

[0095] Step 201, establis...

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Abstract

The invention discloses a multi-unmanned aerial vehicle and user cooperative communication optimization method based on an MAPPO algorithm. The method comprises the following steps: 1, establishing an unmanned aerial vehicle network model and a user network model; 2, setting unmanned aerial vehicle and user scenes; 3, obtaining observation states of the unmanned aerial vehicle and the user; 4, acquiring global states of the unmanned aerial vehicle and the user; 5, obtaining rewards of the unmanned aerial vehicle and the user; 6, storing the experience tuple; 7, iteratively optimizing the parameters of the network model through the MAPPO algorithm; and 8, performing multi-unmanned aerial vehicle and multi-user cooperative communication optimization prediction. According to the invention, through optimization of network model parameters of the unmanned aerial vehicles and the users, optimization of flight azimuth angles, power and bandwidth allocation of the unmanned aerial vehicles is realized, and observation states of multiple unmanned aerial vehicles and multiple users are effectively adapted to predict and output a reasonable cooperative communication optimization strategy; the throughput of the communication system is maximized under the multi-dimensional decision action, and the fairness of resource allocation is met.

Description

technical field [0001] The invention belongs to the technical field of unmanned aerial vehicle and user communication, and in particular relates to a multi-unmanned aerial vehicle and user cooperative communication optimization method based on the MAPPO algorithm. Background technique [0002] In the current 5G mobile communication, with the rapid development of various emerging industries, the terrestrial backbone network is under huge data transmission pressure. At the same time, limited by geographical conditions, many remote areas are still in a state of lack of wireless coverage. These unprecedented demands for high-quality wireless communication services pose serious challenges to the current traditional ground communication networks. For this reason, in the future 6G and beyond wireless communication, UAV (Unmanned Aerial Vehicle, UAV) as an air access node to assist ground communication has become a promising solution. [0003] As a flying base station, UAVs have s...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G05B13/04
CPCG05B13/042
Inventor 赵建伟吴官翰贾维敏张峰干姜楠王连锋谭力宁金伟金国栋沈涛张聪何芳
Owner 中国人民解放军火箭军工程大学
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