Multi-unmanned-aerial-vehicle network cooperative communication method

Abstract

The invention discloses a multi-unmanned-aerial-vehicle network cooperative communication method. The multi-unmanned-aerial-vehicle network cooperative communication method comprises the steps that amaster unmanned aerial vehicle and slave unmanned aerial vehicles start monitoring after flying to a preset flight track according to the preset flight track to collect fire disaster data; according to the distributed link flow, link power and information transmission rate, the slave unmanned aerial vehicles summarize and send the collected data to the master unmanned aerial vehicle in an ad-hoc method; and the master unmanned aerial vehicle sends the collected data to a ground receiving station. According to the communication requirements in fire monitoring, in the unmanned aerial vehicle network with dynamic network topology changes, the communication capability of the network is improved by jointly considering the data acquisition rate control, channel transmission rate arrangement andresource allocation of the unmanned aerial vehicles. The joint information source and channel rate control scheme in the unmanned aerial vehicle fire monitoring network provided by the multi-unmanned-aerial-vehicle network cooperative communication method effectively improves the communication performance of the network, so that technical guarantee is provided in the communication field for the network to be applied to actual fire monitoring, the communication capability of the network is ensured, and the multi-unmanned-aerial-vehicle network cooperative communication method has a great significance for fire rescue.

Description

technical field [0001] The invention relates to the field of rate control in the field of wireless communication, in particular to a multi-unmanned aerial vehicle network cooperative communication method. Background technique [0002] In the urban fire monitoring network composed of drones, the data collection rate and communication rate are controlled according to the network conditions to reduce congestion, so as to assist fire rescue more effectively. When all UAVs collect and send data without restriction at the same time, communication resources will be wasted, and at the same time, serious network congestion will be caused, which will affect the final fire monitoring results and rescue decisions. [0003] At present, research on UAV communication focuses on the performance of the communication system. For example, "Energy-efficient UAV communication with trajectory optimization" studies the joint trajectory optimization and power control of communication from a single ...

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Problems solved by technology

[0005] (1) In the existing schemes, the communication performance optimization of the point-to-point system is studied, and the assistance of other UAVs is not considered. In the fire monitoring scene, due to the occlusion of urban buildings, the quality of the communication link is poor, resulting in point-to-point The network is not up to the task of fire monitoring

[0006] (2) Existing research is carried out in pure communication scenarios. For task-driven networks, it needs to be optimized in combination with task execution requirements, rather than simply considering abstract communication scenarios.

However, in the fire monitoring scenario, the UAV has a fixed monitoring target, so the trajectory of the UAV is also fixed, and the communication performance cannot be improved through trajectory optimization.

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