Time and energy efficient data collection via UAV

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.

Automated summary

This study proposes two schemes for data collection using UAVs, aiming to minimize flight cycle and maximize energy efficiency. The flight cycle is minimized by optimizing wake-up scheduling, trajectory, and time slot. Energy efficiency is maximized by introducing slack variables and applying SCA to approximate the optimization problems. Numerical results show that the flight cycle can be minimized while satisfying the data requirement in the first scheme, and the energy efficiency can be maximized with a trade-off between transmission data and propulsion power consumption in the second scheme.