A Time-Frequency Resource Allocation Method for Unmanned Aerial Vehicle Based on Block Coordinate Descent

Abstract

The present invention provides a UAV time-frequency resource allocation method based on block coordinate descent, and includes the following steps: determining the number of UAVs, setting the system authorized channel set, setting the maximum power limit of the system and other environmental parameters; The spectrum allocation matrix and the adjacent channel interference matrix are introduced into the original problem, and the original complex max-min hybrid programming problem is simplified by using the problem structure characteristics; a low-complexity iterative algorithm based on block coordinate descent is proposed to solve the above problem; the ground According to the maximum SINR value of each drone, the control station allocates power and channel to the drone through the remote control channel, and completes the design of the time-frequency resource allocation method of the drone. The beneficial effects of the present invention are: the UAV time-frequency resource allocation method based on the block coordinate descent shown in the figure can realize limited spectrum resources under the premise of improving the reliability of the control signals received by each UAV and ensuring the maximum power consumption of the system. reasonable distribution.

Description

Technical field [0001] The present invention belongs to the UAV communications technologies, and in particular as a resource allocation method based UAV pilot block coordinates fall. Background technique [0002] With the enhancement of computing power and sensing technologies, unmanned aerial vehicles has become the popular choice in applications such as urban search, military reconnaissance and supervision in agriculture. However, since the UAV wireless services spectrum exponential growth and resource constraints and other challenges, the UAV Communication facing a severe test. Meanwhile, multi-UAV collaboration also brings many challenges to consider. Wherein, a key technical challenge is the safety and stability needs UAV communication control signal itself having a certain robustness, and quality of the control channel signal variations and disturbances are very sensitive; Another challenge is available communication resources are usually limited nature exacerbate potential...

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

Images