A Probabilistic Scheduling Policy for Energy Efficient UAV Communications with Delay Constraints

A typical application of unmanned aerial vehicles (UAVs) is surveillance of distant targets, where data collected by its sensors need to be transmitted back to a ground terminal (GT) for further processing in a timely manner. Due to the limited battery capability of the UAV, the sensed data could be preprocessed in a UAV to reduce the amount of data transmitted, which could potentially reduce the average power consumption at the UAV, especially when the transmission link quality is poor. In this paper, a probabilistic approach is adopted to schedule the transmission and computing of the data tasks based on the UAV and GT's buffer states. The joint transmission and computing problem can be modeled as a four-dimensional Markov chain, based on which the average delay of each task and the average power consumption at the UAV can be obtained. Our design goal is to minimize the average power consumption under the delay constraints. To do that, a delay-constrained power minimization problem is solved by an proposed method to obtain the power-optimal joint transmission and computation scheduling (JTCS) policy efficiently. Finally, the optimization results are validated with extensive simulations.