Unmanned aerial vehicle assisted Internet of Things hostile interference resisting method and system based on reinforcement learning

Abstract

The invention discloses an unmanned aerial vehicle assisted internet of things hostile interference resisting method based on reinforcement learning. The method comprises the following steps: establishing a hostile interference resisting attack and defense Stackelberg game model in which a ground sensor node, an unmanned aerial vehicle and an intelligent jammer are three participants of the game;deducing game equilibrium points in the hostile interference resisting attack and defense Stackelberg game model and existence conditions of the game equilibrium points, wherein the game equilibrium points comprise the optimal interference power of an intelligent jammer, the optimal transmitting power of the unmanned aerial vehicle, the optimal moving distance of the unmanned aerial vehicle and the optimal transmitting power of the ground sensor node; under the condition of an unknown interference model, introducing a WoLF-PHC algorithm to dynamically optimize the transmitting power of the ground sensor node, the transmitting power of an unmanned aerial vehicle and the moving track of the unmanned aerial vehicle. The invention discloses an unmanned aerial vehicle assisted internet of things hostile interference resisting method and system based on reinforcement learning. Intelligent interference with variable interference signal intensity is resisted by adjusting the track or transmitting power of an unmanned aerial vehicle in time.

Description

technical field [0001] The invention relates to the technical field of the Internet of Things, in particular to a UAV-assisted Internet of Things anti-hostile interference method and system based on reinforcement learning. Background technique [0002] Utilizing the controllable mobility of UAVs (unmanned aerial vehicles, UAVs) can solve the problem of limited coverage of the Internet of Things (IoTs), and the combination of IoTs and UAVs can realize more diverse IoT applications . In some places with complex geographical environments, such as disaster areas, highways and busy cities, etc., the direct link from the ground sensor nodes (GSN) to the base station (BS) in the IoT device is damaged, and the UAV can be used as a The relay assists the smooth communication of the ground network. However, the broadcast nature of radio propagation makes UAV communication vulnerable to hostile jamming attacks. Once the wireless link is interfered, normal communication will be affecte...

AI Technical Summary

Problems solved by technology

However, the broadcast nature of radio propagation makes UAV communication vulnerable to hostile jamming attacks. Once the wireless link is interfered, normal communication will be affected

[0003] Existing unmanned aerial vehicles (UAV) anti-hostile jamming schemes usually use a single flight trajectory or frequency hopping strategies, which can resist attacks with fixed jamming power, but are resistant to intelligent jammers (Jammers) with variable jamming signal strength. ) at a loss

Secondly, the existing scheme assumes that the UAV has known information about the changes in the external environment. Due to the time-varying nature of the wireless channel, the high mobility of the UAV, and the variable interference intensity at any time, the UAV cannot accurately obtain information such as the current channel gain or interference signal strength.

Correspondingly, UAVs cannot adjust their trajectory or transmission power in time to resist intelligent interference

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