Abstract

Owing to the rapid development of unmanned aerial vehicles (UAVs), UAV-enabled data collection has emerged as a promising technology. However, for the scenarios where the UAVs are dispatched to gather surrounding information actively and dynamically, the existing data collection methods can hardly fulfill the corresponding demands. To this end, we aim to study the paradigm data acquisition, where the UAV dynamically gathers information by on-board sensors. In this paper, we consider the scenario where a UAV acquires data in real time, which needs to be timely processed with the assistance of a mobile edge computing server. To address the real-time data acquisition characteristics, we construct a novel data acquisition rate model, which is with respect to the UAV speed. Next, we formulate a UAV energy consumption minimization problem that jointly considers UAV trajectory, transmission power, and CPU frequency. To tackle the highly complex problem, we propose an efficient iterative algorithm, and rigorously derive a closed-form solution for the UAV transmission power and computation resources allocation. With the obtained numerical results, we further validate the superiority of the proposed system design and the effectiveness of our algorithm against benchmark schemes.

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