Method for distribution of time-frequency resources of unmanned aerial vehicles based on block coordinate descent

Abstract

The invention provides a method for distribution of time-frequency resources of unmanned aerial vehicles based on block coordinate descent. The method comprises the following steps of determining thenumber of the unmanned aerial vehicles, setting a system authorization channel set, and setting a maximum power upper limit of the system and other environmental parameters; constructing a spectrum allocation matrix and an adjacent channel interference matrix to be introduced into an original problem, and utilizing the structural characteristics of the problem to simplify an original complex max-min hybrid planning problem; providing a low-complexity iterative algorithm based on the block coordinate descent to solve the problem; and making a ground control station carry out power and channel distribution on the unmanned aerial vehicles through a remote control channel according to a maximum SINR value of each unmanned aerial vehicle, and completing the design of the method for distributionof the time-frequency resources of the unmanned aerial vehicles. The method for distribution of the time-frequency resources of the unmanned aerial vehicles based on the block coordinate descent hasthe beneficial effects that the reasonable distribution of the limited frequency spectrum resources is realized on the premise of improving the reliability of a control signal received by each unmanned aerial vehicle and ensuring the maximum consumption power constraint of the system.

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 block coordinate descent. 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 ...

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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