In this paper, we consider the cellular Internet of unmanned aerial vehicles (UAVs), where UAVs sense data with onboard sensors for multiple sensing tasks and transmit the data to the base station (BS). To quantify the 'freshness' of the data at the BS, we bring in the concept of the age of information (AoI). The AoI is determined by the time for UAV sensing and that for UAV transmission, which gives rise to a trade-off within a given period. To minimize the AoI, we formulate a joint sensing time, transmission time, UAV trajectory, and task scheduling optimization problem. This NP-hard problem can be decoupled into two subproblems. We first propose an iterative algorithm to optimize the sensing time, transmission time, and UAV velocity for completing a specific task. Afterwards, we design the order in which the UAV performs data updates for multiple sensing tasks. The convergence and complexity of the proposed algorithm, together with the trade-off between UAV sensing and UAV transmission, are analyzed. Simulation results show that the AoI with the proposed algorithm is about 15% lower than that of the greedy algorithm, and over 40% lower than that of the random algorithm.
All Science Journal Classification (ASJC) codes
- Computer Science Applications
- Electrical and Electronic Engineering
- Applied Mathematics
- Age of information
- cellular Internet of UAVs
- sensing and transmission trade-off