Unmanned aerial vehicle energy consumption minimization design method and device

Abstract

The invention discloses an unmanned aerial vehicle energy consumption minimization design method and device. The method comprises the following steps: calculating channel gains of an unmanned aerial vehicle and a sensor node; calculating energy consumed by communication of the sensor node according to the channel gain of the unmanned aerial vehicle and the sensor node; calculating energy collected by the sensor node according to the channel gain of the unmanned aerial vehicle and the sensor node; calculating energy consumed by the unmanned aerial vehicle; calculating a sensor information age AoI according to the energy consumed by communication of the sensor node and the remaining electric quantity condition of a battery of the sensor node; minimizing the energy consumption of the unmanned aerial vehicle by jointly optimizing the flight path and the flight time of the unmanned aerial vehicle and an information collection and energy collection strategy, and establishing an optimization problem model; establishing an unmanned aerial vehicle control framework based on the DQN; and according to the unmanned aerial vehicle control framework based on the DQN, planning an unmanned aerial vehicle flight strategy based on the DQN.

Description

technical field [0001] The invention relates to the technical field of network optimization design, in particular to a design method and device for minimizing energy consumption of an unmanned aerial vehicle. Background technique [0002] With the rapid deployment of 5G, applications such as virtual reality (VR, Virtual Reality), augmented reality (AR, Augmented Reality), unmanned driving, and smart medical care are booming. Freshness is also very sensitive, and traditional network indicators such as throughput and delay cannot accurately describe the freshness of information in the network. [0003] In order to accurately characterize the freshness of information, the academic community proposes the concept of age of information (AoI, age of information), which is defined as the elapsed time since the latest data packet received by the destination node was generated at the source node. AoI is one of the key performance indicators in sensor networks. In order to ensure the ...

AI Technical Summary

Problems solved by technology

However, the existing system simply discretizes the flight area of ​​the UAV, which cannot avoid the large-angle turning of the UAV during the flight, so the optimization result does not match the actual flight of the UAV.

And it only focuses on how to save energy for drones and sensor nodes, and has not yet introduced wireless radio frequency energy harvesting technology to power low-power sensor nodes

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