Unmanned aerial vehicle base station flight planning method and system, storage medium and unmanned aerial vehicle base station

Abstract

The invention provides an unmanned aerial vehicle base station flight planning method and system, a storage medium and an unmanned aerial vehicle base station. The method comprises the following steps: obtaining the instantaneous secrecy rate of the unmanned aerial vehicle base station and the distance from the unmanned aerial vehicle base station to the end point position in real time through anunmanned aerial vehicle base station operation model adopting a sight distance and non-sight distance mixed channel; performing reinforcement learning by taking the instantaneous secrecy rate as an income, and obtaining an optimized flight path of the unmanned aerial vehicle base station flying from an initial position to a maximum position of the instantaneous secrecy rate; and carrying out reinforcement learning by taking the instantaneous secrecy rate in combination with the distance from the unmanned aerial vehicle base station to the final position as an income, and obtaining an optimizedflight path of the unmanned aerial vehicle base station flying from the position with the maximum instantaneous secrecy rate to the final position.

Description

technical field [0001] The present invention relates to the technical field of wireless communication, and more specifically, to a flight planning method, system, storage medium and UAV base station for an unmanned aerial vehicle base station. Background technique [0002] In recent years, the air base station technology realized by UAV has received sufficient attention and development. Compared with traditional ground communication, UAV base stations fly at a higher altitude, and it is easier to conduct line-of-sight transmission with ground users to improve communication quality. It can be quickly deployed as needed, and has strong applicability to emergency scenarios such as disaster search and rescue. As a UAV platform, the UAV base station has attracted much attention on the optimization of its flight route. At the same time, as a base station platform, how to ensure the security of confidential information during transmission is also a very important practical problem....

AI Technical Summary

Problems solved by technology

[0003] As shown in the Chinese patent with publication date of 2020.06.26 and publication number CN 111343712 A: A UAV-assisted Cognitive Wireless Network Communication Security Control Method, the current prior art generally uses continuous convex approximation and block coordinate descent The optimal trajectory obtained in this way is fixed and offline, which also means that a large amount of calculation work is required in the early stage; in addition, the existing technology usually only considers line-of-sight transmission, which is also divorced from the actual environment. Obvious limitations

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