Abstract
An unmanned aerial vehicle (UAV) aided wireless powered mobile edge computing (MEC) system is considered in this paper. Different from most existing works that only consider the information transmission assisted by the UAV, in the studied model, the UAV can not only act as an information relay to help the mobile users (MUs) to offload their computation tasks to the MEC server, but also broadcast energy to MUs. This is significant in situations where the target area is experiencing communications and power outage due to an emergency such as an earthquake. The objective of the paper is to maximize the sum of the MU’s complete task-input bits by jointly optimizing the time allocation, the UAV’s energy transmit power, and the UAV’s trajectory under a given time duration. The problem is formulated as an optimization problem, which is non-convex and difficult to solve directly. To solve this problem, a block coordinate descending algorithm is proposed, which solves two sub-problems iteratively until convergence. Simulation results indicate that the trajectories of the UAV rely highly on the positions of the MUs and the MEC server, and the proposed algorithm has superior performance comparing with two benchmark algorithms under different conditions.
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Notes
- 1.
For simplicity, \(\forall n\) and \(\forall k\) denote \(\forall n \in \mathcal {N}\) and \(\forall k \in \mathcal {K}\), respectively.
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Acknowledgement
This work is partly supported by the Natural Science Foundation of Guangdong Province under grant 2021A1515011856, and the National Natural Science Foundation of China under grant U1801261.
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Wang, H., Shen, Y., Wu, S., Wang, S. (2021). Resource Allocation and Trajectory Optimization for UAV Assisted Mobile Edge Computing Systems with Energy Harvesting. In: Zhang, H., Yang, Z., Zhang, Z., Wu, Z., Hao, T. (eds) Neural Computing for Advanced Applications. NCAA 2021. Communications in Computer and Information Science, vol 1449. Springer, Singapore. https://doi.org/10.1007/978-981-16-5188-5_30
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