Abstract
Using unmanned aerial vehicles (UAVs) for data collection has emerged as a promising technique to achieve both time- and energy-efficient data gathering while keeping data fresh. In this study, two schemes are proposed for flight cycle minimization and energy efficiency maximization to collect data from ground sensors. We first minimize the flight cycle by jointly optimizing the wake-up scheduling of sensors, the trajectory, and the time slot, which is a mixed-integer non-convex problem and difficult to solve directly. To this end, we propose an iterative algorithm based on block coordinate descent and successive convex approximation to decouple the original non-convex problem into two sub-problems and the constraints are turned to be convex approximately. Furthermore, the energy efficiency is maximized since the limited energy is a critical issue in UAV communication systems. We approximate the two subproblems as convex optimizations by introducing slack variables and applying SCA. The approximate energy efficiency is a fractional expression, and we use Dinkelbach’s method to solve it. Numerical results show that the flight cycle is minimized in the first scheme with the data requirement satisfied, while in the second scheme, the energy efficiency is maximized with the trade-off between the transmission data and the propulsion power consumption.
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This work was supported by National Key R&D Program of China (Grant No. 2020YFB1807002).
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Wang, T., Pang, X., Tang, J. et al. Time and energy efficient data collection via UAV. Sci. China Inf. Sci. 65, 182302 (2022). https://doi.org/10.1007/s11432-021-3343-7
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DOI: https://doi.org/10.1007/s11432-021-3343-7