Unmanned aerial vehicle and ground base station cooperative computing unloading and optimizing method

Abstract

The invention discloses an unmanned aerial vehicle and ground base station cooperative computing unloading and optimizing method, which comprises the following steps of: firstly, according to the distribution condition of mobile equipment, drawing an unmanned aerial vehicle initial track, and setting error tolerance according to actual requirements; setting an iteration parameter z; fixing the moving track of the unmanned aerial vehicle, and optimizing the bit allocation of the bandwidth; fixing the optimized bandwidth and bit allocation, and optimizing the moving trajectory of the unmanned aerial vehicle; the optimized moving track is compared with the previous moving track, and if the optimized moving track is within the error tolerance, acquiring the optimal track; otherwise, adding oneto the iteration parameter, and repeating the above steps. According to the cooperative computing unloading method, computing resources of the unmanned aerial vehicle and the ground base station canbe utilized to a greater extent, so that the energy consumption is reduced, and the stability of a communication channel and the popularization of unmanned aerial vehicle auxiliary mobile edge computing are facilitated.

Description

technical field [0001] The invention belongs to the field of information technology, in particular to a calculation and optimization method for introducing an auxiliary edge of an unmanned aerial vehicle into a cellular network. Background technique [0002] In traditional terrestrial cellular networks, mobile devices at the edge often have poor channel conditions. The introduction of unmanned aerial vehicles will undoubtedly improve the reliability of communication links. However, computing offload is limited by the battery life of mobile devices and drones, and the overall energy consumption is relatively high. [0003] Existing research is based on ground base stations and mobile devices, or based on communication between UAVs and mobile devices. The former is to divide the area covered by each ground base station, and the mobile devices in the area will offload the calculation tasks to the base station, and the base station will perform data calculation and processing, ...

AI Technical Summary

Problems solved by technology

Moreover, the size of the UAV also determines that it is impossible to deploy edge servers with high computing resources

[0004] To sum up, the existing research results do not solve the joint optimization problem of computing offloading of mobile devices and energy consumption of UAVs.

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