Resource allocation for a UAV-enabled mobile- edge computing system: Computation efficiency maximization

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Abstract

Energy-efficient computation is important in mobile edge computing (MEC) systems. However, the computation efficiency problem in the unmanned aerial vehicle (UAV)-enabled MEC systems has been rarely researched. In this paper, a UAV-enabled MEC system under partial computation offloading mode is investigated. The computation efficiency is maximized by jointly optimizing the offloading times, the central processing unit frequencies, the transmit powers of the user and the trajectory of the UAV. For the non-convex computation efficiency problem, a two-stage iterative algorithm is proposed. Moreover, we derive the closed-form expressions for the local computation frequency and the transmit power of the user, which facilitates our algorithm implementation. Simulation results demonstrate that the computation efficiency of our proposed joint optimization scheme is better than those of other benchmark schemes.

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Zhang, X., Zhong, Y., Liu, P., Zhou, F., & Wang, Y. (2019). Resource allocation for a UAV-enabled mobile- edge computing system: Computation efficiency maximization. IEEE Access, 7, 113345–113354. https://doi.org/10.1109/ACCESS.2019.2935217

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