Unmanned aerial vehicle time-frequency resource allocation method based on gradient projection

Abstract

The invention provides an unmanned aerial vehicle time-frequency resource allocation method based on gradient projection. The method comprises the following steps: determining amount of unmanned aerial vehicle, setting a system authorization channel set, setting a system maximum power upper limit and other environment parameters; constructing a spectrum allocation matrix and an adjacent channel matrix to introduce the original problem, simplifying max-min hybrid planning problem which is originally complex by using problem structural characteristics. An iteration algorithm of the gradient projection is proposed to solve the problem; a ground control station performs power and channel allocation on the unmanned aerial vehicle through a remote channel according to the maximum SINR value of each unmanned aerial vehicle, thereby finishing the unmanned aerial time-frequency resource allocation method design. The method provided by the invention has the advantages that the reasonable allocation of the limited spectrum resource is realized in the premise of improving the reliability of a control signal received by each unmanned aerial vehicle and guaranteeing the maximum consumption powerconstraint of the system through the unmanned aerial vehicle time-frequency resource allocation method based on the gradient projection.

Description

technical field [0001] The invention belongs to the technical field of unmanned aerial vehicle communication, and specifically relates to a method for allocating time-frequency resources of an unmanned aerial vehicle based on gradient projection. Background technique [0002] With the improvement of sensing technology and computing power, drones are gradually becoming a common choice in applications such as urban search, military reconnaissance and agricultural supervision. However, due to challenges such as the exponential growth of UAV wireless service demand and the shortage of spectrum resources, UAV communication is facing a severe test. At the same time, the collaborative operation of multiple UAVs also brings many challenges that need to be considered. Among them, a key technical challenge is that the security and stability of UAV communication requires a certain robustness of the control signal itself, and the quality of the control signal is very sensitive to chann...

AI Technical Summary

Problems solved by technology

However, due to challenges such as the exponential growth of UAV wireless service demand and the shortage of spectrum resources, UAV communication is facing a severe test

At the same time, the collaborative operation of multiple UAVs also brings many challenges that need to be considered

Among them, a key technical challenge is that the security and stability of UAV communication requires a certain robustness of the control signal itself, and the quality of the control signal is very sensitive to channel changes and interference; another challenge is, The resources available for communication are often finite, exacerbating potential mutual interference effects

[0003] However, none of the existing work has studied how to improve the utilization of UAV spectrum resources and the allocation of limited time-frequency resources for multi-UAV systems

In fact, the UAV's control signal reception is not only affected by the link quality of the communication channel, but also easily affected by potential interference

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